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Unstaged changes:
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_A_antarctica_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_P_australis_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_Z_marina_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_Z_muelleri_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_only_in_Algae.txt
    Modified:   data/Lost_present_gene_lists/Genes_only_in_Aquatics_and_Seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_only_in_Aquatics_and_Seagrasses_and_Terrestrials.txt
    Modified:   data/Lost_present_gene_lists/Genes_only_in_Duckweeds.txt
    Modified:   data/Lost_present_gene_lists/Genes_only_in_Seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_only_in_Terrestrials.txt
    Modified:   data/Lost_present_gene_lists/Genes_union_of_Seagrass_and_Aquatics_union.txt
    Modified:   data/arabidopsis_gene_level_comparison.xlsx
    Modified:   data/arabidopsis_gene_level_comparison_only_losts.xlsx
    Modified:   data/arabidopsis_gene_level_counts.xlsx
    Modified:   output/GO_results_genes_in_Aquatics_and_Seagrasses_NOT_Terrestrials.csv
    Modified:   output/GO_results_genes_in_Duckweeds_NOT_Algae_NOT_Seagrasses_NOT_Terrestrials.csv
    Modified:   output/GO_results_genes_in_Seagrasses_NOT_Algae_NOT_Duckweeds_NOT_Terrestrials.csv
    Modified:   output/GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv
    Modified:   output/GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv
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library(topGO)
Warning: package 'S4Vectors' was built under R version 4.1.1
Warning: package 'SparseM' was built under R version 4.1.1
library(tidyverse)
Warning: package 'tidyverse' was built under R version 4.1.2
Warning: package 'ggplot2' was built under R version 4.1.1
Warning: package 'tibble' was built under R version 4.1.1
Warning: package 'tidyr' was built under R version 4.1.1
Warning: package 'readr' was built under R version 4.1.2
Warning: package 'purrr' was built under R version 4.1.1
Warning: package 'dplyr' was built under R version 4.1.1
Warning: package 'stringr' was built under R version 4.1.1
Warning: package 'forcats' was built under R version 4.1.1
library(rvest)
Warning: package 'rvest' was built under R version 4.1.1
library(wesanderson)
Warning: package 'wesanderson' was built under R version 4.1.1
library(httr)
Warning: package 'httr' was built under R version 4.1.1
library(stringi)
Warning: package 'stringi' was built under R version 4.1.1
library(ggrepel)
Warning: package 'ggrepel' was built under R version 4.1.1
library(eulerr)
Warning: package 'eulerr' was built under R version 4.1.1
library(UpSetR)
Warning: package 'UpSetR' was built under R version 4.1.1
library(rrvgo)
library(kableExtra)
Warning: package 'kableExtra' was built under R version 4.1.2
library(patchwork)
Warning: package 'patchwork' was built under R version 4.1.1
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())

Lost in seagrasses

The GO enrichment does not work well on my laptop so I’m setting this to eval=FALSE and run it on a remote server.

This document takes the output of Orthofinder

# give properly formatted background in format: GO:0005838  GSBRNA2T00088508001;GSBRNA2T00088313001;GSBRNA2T00035842001 
#annAT <- readMappings('BACKGROUND.txt.gz', sep="\t", IDsep=";")
#save(annAT, file='annAtObject.RData')

load('annAtObject.RData')
allgenes <- unique(unlist(annAT))

compare <- function(genelistfile, outname, allgenes, annAT) {
  # give file with your genes of interest, one gene_id per line
  
  mygenes <-scan(genelistfile ,what="")
  geneList <- factor(as.integer(allgenes %in% mygenes))
  names(geneList) <- allgenes
  
  GOdata <-new ("topGOdata", ontology = 'BP', allGenes = geneList, nodeSize = 5, annot=annFUN.GO2genes, GO2genes=annAT)
  # using ClassicCount:
  #test.stat <-new ("classicCount", testStatistic = GOFisherTest, name = "Fisher Test")
  #resultsFisherC <-getSigGroups (GOdata, test.stat)
  # using weight01:
  weight01.fisher <- runTest(GOdata, statistic = "fisher")
  # using ClassicCount:
  # allRes <- GenTable(GOdata, classicFisher= resultsFisherC, topNodes = 30)
  # using weight01:
  allRes <- GenTable(GOdata, classicFisher=weight01.fisher,topNodes=30)#,topNodes=100)
  names(allRes)[length(allRes)] <- "p.value"
  p_values <- score(weight01.fisher)
  adjusted_p <- p.adjust(p_values)
  adjusted_p[adjusted_p < 0.05] %>% enframe() %>% write_csv('data/' + outname)

}

Comparing the four big groups

# all genes shared - this runs out of memory
#compare('Lost_present_gene_lists/Genes_only_in_Aquatics_and_Seagrasses_and_Terrestrials.txt', 'output/GO_results_genes_in_Aquatics_and_Seagrasses_and_Terrestrials.csv', allgenes, annAT)

# Genes in aquatics and seagrasses - IMPORTANT This is NOT the union - this is the intersection!
# Union is below
compare('Lost_present_gene_lists/Genes_only_in_Aquatics_and_Seagrasses.txt', 'output/GO_results_genes_in_Aquatics_and_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in algae
compare('Lost_present_gene_lists/Genes_only_in_Algae.txt', 'output/GO_results_genes_in_Algae_NOT_Duckweeds_NOT_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in seagrasses
compare('Lost_present_gene_lists/Genes_only_in_Seagrasses.txt', 'output/GO_results_genes_in_Seagrasses_NOT_Algae_NOT_Duckweeds_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in duckweeds
compare('Lost_present_gene_lists/Genes_only_in_Duckweeds.txt', 'output/GO_results_genes_in_Duckweeds_NOT_Algae_NOT_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in terrestrials
compare('Lost_present_gene_lists/Genes_only_in_Terrestrials.txt', 'output/GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv', allgenes, annAT)

# Genes union of Seagrass and Aquatics
compare('Lost_present_gene_lists/Genes_union_of_Seagrass_and_Aquatics_union.txt', 'output/GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)


# Genes only in seagrasses- seagrass-specific
compare('Lost_present_gene_lists/Genes_in_all_seagrasses_intersect.txt', 'output/GO_results_genes_in_all_seagrasses_vs_backgroundAll_intersect.csv', allgenes, annAT)

compare('Lost_present_gene_lists/Genes_in_all_seagrasses_union.txt', 'output/GO_results_genes_in_all_seagrasses_vs_backgroundAll_union.csv', allgenes, annAT)

Seagrass only comparisons

Now we compare seagrasses within each other.

For the seagrass-only comparisons, I’m using a Seagrass-only background as that makes more biological sense to me.s

# give properly formatted background in format: GO:0005838  GSBRNA2T00088508001;GSBRNA2T00088313001;GSBRNA2T00035842001 
#sannAT <- readMappings('SEAGRASSBACKGROUND.txt', sep="\t", IDsep=";")  
#save(sannAT, file='sannAtObject.RData')

load('sannAtObject.RData')
sallgenes <- unique(unlist(sannAT))

lost in seagrasses

compare('Lost_present_gene_lists/Genes_lost_in_A_antarctica_not_other_seagrasses.txt', 'output/GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_lost_in_Z_marina_not_other_seagrasses.txt', 'output/GO_results_genes_lost_Z_marina_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_lost_in_P_australis_not_other_seagrasses.txt', 'output/GO_results_genes_lost_P_australis_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_lost_in_Z_muelleri_not_other_seagrasses.txt', 'output/GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv', sallgenes, sannAT)

Present in seagrasses

compare('Lost_present_gene_lists/Genes_in_all_seagrasses_intersect.txt', 'output/GO_results_genes_in_all_seagrasses_vs_seagrassesBackground_intersect.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_in_all_seagrasses_union.txt', 'output/GO_results_genes_in_all_seagrasses_vs_seagrassesBackground_union.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_Z_marina_not_other_seagrasses.txt', 'output/GO_results_genes_only_Z_marina_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_Z_muelleri_not_other_seagrasses.txt', 'output/GO_results_genes_only_Z_muelleri_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_P_australis_not_other_seagrasses.txt', 'output/GO_results_genes_only_P_australis_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_A_antarctica_not_other_seagrasses.txt', 'output/GO_results_genes_only_A_antarctica_not_other_seagrasses.csv', sallgenes, sannAT)

Alright now we have all these different GO terms in all these files - we can send them to revigo for visualiation and some deduplication!

Revigo

This code is based on http://revigo.irb.hr/CodeExamples/revigo.R.txt

results_list <- list()

for (f in list.files('./output/', pattern='*.csv')){
  filename <- paste('./output/', f, sep='')
  go_and_pvalues <- readChar(filename, file.info(filename)$size)
  go_and_pvalues <- gsub(',', ' ', go_and_pvalues)
  
  httr::POST(
    url = "http://revigo.irb.hr/StartJob.aspx",
    body = list(
      cutoff = "0.7",
      valueType = "pvalue",
     # speciesTaxon = "4577", # zea mays
     #speciesTaxon = '39947', # japonica
     speciesTaxon = '3702', # arabidopsis
      measure = "SIMREL",
      goList = go_and_pvalues
    ),
    # application/x-www-form-urlencoded
    encode = "form"
  ) -> res
  
  dat <- httr::content(res, encoding = "UTF-8")
  
  jobid <- jsonlite::fromJSON(dat,bigint_as_char=TRUE)$jobid
  
  # Check job status
  running <- "1"
  while (running != "0" ) {
      httr::POST(
        url = "http://revigo.irb.hr/QueryJobStatus.aspx",
        query = list( jobid = jobid )
      ) -> res2
      dat2 <- httr::content(res2, encoding = "UTF-8")
      running <- jsonlite::fromJSON(dat2)$running
      Sys.sleep(1)
  }
  
  # Fetch results
  httr::POST(
    url = "http://revigo.irb.hr/ExportJob.aspx",
    query = list(
      jobid = jobid, 
      namespace = "1",
      type = "CSVTable"
    )
  ) -> res3
  
  dat3 <- httr::content(res3, encoding = "UTF-8")
  
  dat3 <- stri_replace_all_fixed(dat3, "\r", "")
  # Now we have a csv table in a string!

  # read_csv does not like the ', ', it wants ','
  dat <- read_csv(gsub(', ', ',', dat3), show_col_types = FALSE) 
  
  # do we even have results?
  if(nrow(dat) == 0){next}
  results_list[[f]] <- dat
  
}
Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

OK we have a list with all results in a big list. Now we can plot!

# lots of warnings and messages here so I'm hiding these
plot_list <- list()
for (f in names(results_list)) {
  dat <- results_list[[f]]
  if(nrow(dat) == 0) {next}
  
  names(dat) <- c("term_ID","description","frequency", 'plot_X', 'plot_Y', 'log_size', 'value', 'uniqueness', 'dispensability', 'eliminated', 'representative')
  one.data <- dat
  if (one.data[1,] == '<html>') {next} # some datasets result in error
  one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null") & (! is.na(one.data$frequency)) & (one.data$value != 'null'), ];
  one.data <- suppressMessages(type_convert(one.data)) # guess data types, but also: shush
  top_ten_values <- one.data %>% arrange(value) %>% head(8) %>% pull(term_ID) 
  
  one.data <- one.data %>% mutate(description2 = case_when(
    term_ID %in% top_ten_values ~ str_wrap(description, width=10), 
    TRUE ~ ''))
  p1 <-
    ggplot(data = one.data, aes(plot_X, plot_Y, label = description2)) +
    geom_point(aes(colour = value, size = log_size), alpha = I(0.6)) +
    scale_size_area() +
    scale_colour_gradientn(colours = rev(wes_palette("Zissou1", 100, type = "continuous")), 
                           limits = c(min(one.data$value), 0)) +
    geom_point(
      aes(plot_X, plot_Y, size = log_size),
      shape = 21,
      fill = "transparent",
      colour = I (alpha ("black", 0.6))
    ) +
    scale_size_area() +
    geom_label_repel(max.overlaps=15,
                     point.padding = 0,
                     min.segment.length = 0, # draw all line segments
                     aes(point.size=log_size), alpha=0.9) + 
    theme_minimal() +
    labs(color = 'log(p-value)',
         size = 'Frequency') +
    theme(
      axis.text.x = element_blank(),
      axis.ticks.x = element_blank(),
      axis.text.y = element_blank(),
      axis.ticks.y = element_blank(),
      axis.title.x = element_blank(),
      axis.title.y = element_blank()
    ) +
    NULL
    #ggtitle(f)
  
  plot_list[[f]] <- p1
  
}

Making Supplementary Tables for the REVIGO results

Let’s also pull these terms out as tables. Value is the unadjusted p-value (-3.7 = 10 * -3.7)

for( i in names(results_list)) {
  print(i)
  print(results_list[[i]] %>% dplyr::filter(Eliminated == FALSE) %>% dplyr::select(TermID, Name, Value) %>% arrange(Value) %>% kbl() %>%  kable_styling())
  cat("\n")
}
[1] “GO_results_genes_in_Algae_NOT_Duckweeds_NOT_Seagrasses_NOT_Terrestrials.csv”
TermID Name Value
GO:0001666 response to hypoxia -23.687536
GO:0006869 lipid transport -22.966618
GO:0009753 response to jasmonic acid -18.865512
GO:0009416 response to light stimulus -18.213656
GO:0009723 response to ethylene -17.628213
GO:0006396 RNA processing -15.439100
GO:0050821 protein stabilization -14.262857
GO:0042254 ribosome biogenesis -12.104152
GO:0006606 protein import into nucleus -11.449685
GO:0009093 cysteine catabolic process -7.106520
GO:0090143 nucleoid organization -6.582460
GO:0042814 monopolar cell growth -5.909563
GO:0035556 intracellular signal transduction -4.590709
GO:0070940 dephosphorylation of RNA polymerase II C-terminal domain -4.439686
GO:0006636 unsaturated fatty acid biosynthetic process -2.423227
GO:0048441 petal development -1.882953
GO:0042759 long-chain fatty acid biosynthetic process -1.819662
GO:0001101 response to acid chemical -1.683709
[1] “GO_results_genes_in_all_seagrasses_vs_backgroundAll_intersect.csv”
TermID Name Value
GO:0042908 xenobiotic transport -4.625900
GO:0060416 response to growth hormone -3.820881
GO:0060919 auxin influx -3.685298
GO:0008283 cell population proliferation -2.979453
GO:0031338 regulation of vesicle fusion -2.839561
GO:0040008 regulation of growth -2.211162
GO:0009827 plant-type cell wall modification -2.084195
GO:0010256 endomembrane system organization -2.057970
GO:0071359 cellular response to dsRNA -2.019432
GO:0040029 regulation of gene expression,epigenetic -1.948428
GO:0048481 plant ovule development -1.938183
GO:0007164 establishment of tissue polarity -1.893452
GO:0034644 cellular response to UV -1.812392
GO:0060321 acceptance of pollen -1.681151
GO:0007033 vacuole organization -1.662324
GO:0071480 cellular response to gamma radiation -1.535639
GO:0000724 double-strand break repair via homologous recombination -1.376381
GO:0046854 phosphatidylinositol phosphate biosynthetic process -1.313884
[1] “GO_results_genes_in_all_seagrasses_vs_backgroundAll_union.csv”
TermID Name Value
GO:0006278 RNA-dependent DNA biosynthetic process -95.746746
GO:0032197 transposition,RNA-mediated -92.360758
GO:0090501 RNA phosphodiester bond hydrolysis -70.168168
GO:0006508 proteolysis -10.679936
GO:0030837 negative regulation of actin filament polymerization -3.229438
GO:0009660 amyloplast organization -3.097832
GO:0010098 suspensor development -3.003551
GO:0010726 positive regulation of hydrogen peroxide metabolic process -2.841104
GO:0040029 regulation of gene expression,epigenetic -2.422445
GO:0010090 trichome morphogenesis -2.345940
GO:0042908 xenobiotic transport -2.177716
GO:0006887 exocytosis -2.036173
GO:0071359 cellular response to dsRNA -1.996182
GO:1904580 regulation of intracellular mRNA localization -1.965042
GO:0051214 RNAi-mediated antiviral immunity against RNA virus -1.874606
GO:0001896 autolysis -1.804933
GO:0043386 mycotoxin biosynthetic process -1.804933
GO:0000905 sporocarp development involved in asexual reproduction -1.804933
GO:0075307 positive regulation of conidium formation -1.804933
GO:0010914 positive regulation of sterigmatocystin biosynthetic process -1.804933
GO:0060416 response to growth hormone -1.778530
GO:0033234 negative regulation of protein sumoylation -1.707895
GO:0007033 vacuole organization -1.459190
[1] “GO_results_genes_in_all_seagrasses_vs_seagrassesBackground_intersect.csv”
TermID Name Value
GO:0010628 positive regulation of gene expression -5.518397
GO:0009651 response to salt stress -4.727278
GO:0009809 lignin biosynthetic process -3.637392
GO:0008283 cell population proliferation -3.523095
GO:0009734 auxin-activated signaling pathway -3.031127
GO:0009407 toxin catabolic process -2.807098
GO:2000031 regulation of salicylic acid mediated signaling pathway -2.443163
GO:2001038 regulation of cellular response to drug -2.440891
GO:0009637 response to blue light -2.321809
GO:0007131 reciprocal meiotic recombination -2.289608
GO:0031338 regulation of vesicle fusion -1.967975
GO:0048527 lateral root development -1.750860
GO:0006355 regulation of transcription,DNA-templated -1.581715
GO:0048366 leaf development -1.546114
GO:0010048 vernalization response -1.412876
GO:0071577 zinc ion transmembrane transport -1.347006
[1] “GO_results_genes_in_all_seagrasses_vs_seagrassesBackground_union.csv”
TermID Name Value
GO:0006355 regulation of transcription,DNA-templated -9.463325
[1] “GO_results_genes_in_Aquatics_and_Seagrasses_NOT_Terrestrials.csv”
TermID Name Value
GO:0006518 peptide metabolic process -5.756991
GO:0006508 proteolysis -4.306535
[1] “GO_results_genes_in_Aquatics_NOT_Seagrasses_NOT_Terrestrials.csv”
TermID Name Value
GO:0010025 wax biosynthetic process -26.626443
GO:0019432 triglyceride biosynthetic process -25.954024
GO:0048438 floral whorl development -25.054223
GO:0009753 response to jasmonic acid -13.955898
GO:0017148 negative regulation of translation -13.764822
GO:2000117 negative regulation of cysteine-type endopeptidase activity -12.436518
GO:0006869 lipid transport -10.654295
GO:0009723 response to ethylene -10.158676
GO:0090696 post-embryonic plant organ development -9.654049
GO:0001666 response to hypoxia -9.070723
GO:0001101 response to acid chemical -8.606000
GO:0034605 cellular response to heat -8.228346
GO:0010373 negative regulation of gibberellin biosynthetic process -7.331038
GO:0010208 pollen wall assembly -6.453670
GO:0009266 response to temperature stimulus -6.229266
GO:0010030 positive regulation of seed germination -6.157498
GO:0006606 protein import into nucleus -5.868931
GO:0019365 pyridine nucleotide salvage -5.687459
GO:0042254 ribosome biogenesis -5.646111
GO:0010220 positive regulation of vernalization response -5.563470
GO:0006355 regulation of transcription,DNA-templated -4.209775
GO:0009910 negative regulation of flower development -3.634419
GO:0048441 petal development -3.509074
GO:0006396 RNA processing -3.319062
GO:0090143 nucleoid organization -3.064675
GO:0009416 response to light stimulus -2.859747
GO:0010262 somatic embryogenesis -2.802825
GO:0032353 negative regulation of hormone biosynthetic process -2.781174
GO:0050821 protein stabilization -2.655356
GO:0009650 UV protection -2.631031
GO:0006212 uracil catabolic process -2.393548
GO:0009093 cysteine catabolic process -2.271820
GO:0048830 adventitious root development -2.256427
GO:0009739 response to gibberellin -1.992537
GO:0042814 monopolar cell growth -1.754299
GO:0072699 protein localization to cortical microtubule cytoskeleton -1.754299
GO:0085029 extracellular matrix assembly -1.708512
GO:0010077 maintenance of inflorescence meristem identity -1.620899
GO:0055046 microgametogenesis -1.407736
[1] “GO_results_genes_in_Duckweeds_NOT_Algae_NOT_Seagrasses_NOT_Terrestrials.csv”
TermID Name Value
GO:0019432 triglyceride biosynthetic process -33.813568
GO:0010025 wax biosynthetic process -32.926365
GO:0048438 floral whorl development -17.642357
GO:0010373 negative regulation of gibberellin biosynthetic process -10.051932
GO:0019365 pyridine nucleotide salvage -7.869478
GO:2000117 negative regulation of cysteine-type endopeptidase activity -7.754562
GO:0010220 positive regulation of vernalization response -6.314980
GO:0009739 response to gibberellin -6.108781
GO:0017148 negative regulation of translation -5.650236
GO:0032353 negative regulation of hormone biosynthetic process -5.368296
GO:0006212 uracil catabolic process -4.732790
GO:0010262 somatic embryogenesis -4.410872
GO:0010030 positive regulation of seed germination -3.709106
GO:0006355 regulation of transcription,DNA-templated -3.649898
GO:0009266 response to temperature stimulus -3.118165
GO:0010077 maintenance of inflorescence meristem identity -3.006104
GO:0070987 error-free translesion synthesis -2.670402
GO:0055046 microgametogenesis -2.612899
GO:0009910 negative regulation of flower development -2.484882
GO:0034605 cellular response to heat -2.354720
GO:0009650 UV protection -1.982601
GO:0009733 response to auxin -1.896062
GO:0006517 protein deglycosylation -1.723037
GO:1903086 negative regulation of sinapate ester biosynthetic process -1.323627
[1] “GO_results_genes_in_Seagrasses_NOT_Algae_NOT_Duckweeds_NOT_Terrestrials.csv”
TermID Name Value
GO:0006278 RNA-dependent DNA biosynthetic process -16.755337
GO:0032197 transposition,RNA-mediated -16.198616
GO:0090501 RNA phosphodiester bond hydrolysis -12.740332
GO:0051603 proteolysis involved in cellular protein catabolic process -10.851966
GO:0033275 actin-myosin filament sliding -6.381585
GO:0043007 maintenance of rDNA -6.273778
GO:0033298 contractile vacuole organization -5.376566
GO:0032060 bleb assembly -5.376566
GO:0050982 detection of mechanical stimulus -5.174384
GO:1900049 regulation of histone exchange -4.893165
GO:0016131 brassinosteroid metabolic process -4.666937
GO:1902466 positive regulation of histone H3-K27 trimethylation -4.431534
GO:0051591 response to cAMP -4.306981
GO:0001932 regulation of protein phosphorylation -3.771625
GO:0080156 mitochondrial mRNA modification -3.501516
GO:0032989 cellular component morphogenesis -3.486473
GO:0006468 protein phosphorylation -3.306015
GO:0048578 positive regulation of long-day photoperiodism,flowering -3.165051
GO:0097193 intrinsic apoptotic signaling pathway -2.858966
GO:0016575 histone deacetylation -2.853274
GO:0006508 proteolysis -2.758813
GO:0009048 dosage compensation by inactivation of X chromosome -2.649480
GO:0090701 specification of plant organ identity -2.628394
GO:0010022 meristem determinacy -2.575176
GO:0045332 phospholipid translocation -2.328497
GO:0006971 hypotonic response -2.181874
GO:0051707 response to other organism -2.021690
GO:0010090 trichome morphogenesis -1.975281
GO:0051555 flavonol biosynthetic process -1.872846
GO:1904872 regulation of telomerase RNA localization to Cajal body -1.838387
GO:0051127 positive regulation of actin nucleation -1.778757
GO:0097242 amyloid-beta clearance -1.619955
GO:0010992 ubiquitin recycling -1.619955
GO:0010815 bradykinin catabolic process -1.619955
GO:0048194 Golgi vesicle budding -1.593843
GO:2001240 negative regulation of extrinsic apoptotic signaling pathway in absence of ligand -1.543011
GO:0071048 nuclear retention of unspliced pre-mRNA at the site of transcription -1.394680
GO:0016926 protein desumoylation -1.393209
GO:0010222 stem vascular tissue pattern formation -1.304595
[1] “GO_results_genes_in_Seagrasses_NOT_Aquatics_NOT_Terrestrials.csv”
TermID Name Value
GO:0051603 proteolysis involved in cellular protein catabolic process -11.456833
GO:0006278 RNA-dependent DNA biosynthetic process -9.577934
GO:0032197 transposition,RNA-mediated -9.168511
GO:0033275 actin-myosin filament sliding -6.682353
GO:0090501 RNA phosphodiester bond hydrolysis -6.648430
GO:0043007 maintenance of rDNA -6.455202
GO:0033298 contractile vacuole organization -5.583611
GO:0032060 bleb assembly -5.583611
GO:0050982 detection of mechanical stimulus -5.431629
GO:1900049 regulation of histone exchange -5.042366
GO:0016131 brassinosteroid metabolic process -4.909247
GO:1902466 positive regulation of histone H3-K27 trimethylation -4.579819
GO:0051591 response to cAMP -4.509703
GO:0001932 regulation of protein phosphorylation -3.934885
GO:0032989 cellular component morphogenesis -3.724531
GO:0048578 positive regulation of long-day photoperiodism,flowering -3.385409
GO:0006468 protein phosphorylation -3.226314
GO:0080156 mitochondrial mRNA modification -3.221374
GO:0097193 intrinsic apoptotic signaling pathway -3.003236
GO:0009048 dosage compensation by inactivation of X chromosome -2.792735
GO:0090701 specification of plant organ identity -2.713400
GO:0010022 meristem determinacy -2.675579
GO:0006971 hypotonic response -2.372108
GO:0010090 trichome morphogenesis -2.336224
GO:0051707 response to other organism -2.284036
GO:0051555 flavonol biosynthetic process -2.102840
GO:1904872 regulation of telomerase RNA localization to Cajal body -1.978326
GO:0051127 positive regulation of actin nucleation -1.905381
GO:0097242 amyloid-beta clearance -1.718349
GO:0010992 ubiquitin recycling -1.718349
GO:0010815 bradykinin catabolic process -1.718349
GO:2001240 negative regulation of extrinsic apoptotic signaling pathway in absence of ligand -1.641177
GO:0016926 protein desumoylation -1.543029
GO:0071048 nuclear retention of unspliced pre-mRNA at the site of transcription -1.532452
GO:0010222 stem vascular tissue pattern formation -1.487551
GO:0010492 maintenance of shoot apical meristem identity -1.433920
GO:0048576 positive regulation of short-day photoperiodism,flowering -1.364131
GO:0043086 negative regulation of catalytic activity -1.351735
GO:0031154 culmination involved in sorocarp development -1.309504
[1] “GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv”
TermID Name Value
GO:0051762 sesquiterpene biosynthetic process -142.090588
GO:0006952 defense response -124.457182
GO:0010082 regulation of root meristem growth -106.689889
GO:2000280 regulation of root development -84.385227
GO:0007165 signal transduction -78.545901
GO:0046345 abscisic acid catabolic process -57.062877
GO:0000966 RNA 5’-end processing -55.681463
GO:0031146 SCF-dependent proteasomal ubiquitin-dependent protein catabolic process -51.086468
GO:0048509 regulation of meristem development -50.165590
GO:0010469 regulation of signaling receptor activity -42.048634
GO:0045338 farnesyl diphosphate metabolic process -41.131763
GO:2000026 regulation of multicellular organismal development -38.143204
GO:0051554 flavonol metabolic process -37.394473
GO:0080156 mitochondrial mRNA modification -35.594730
GO:0009819 drought recovery -35.457057
GO:0019756 cyanogenic glycoside biosynthetic process -34.774947
GO:0080003 thalianol metabolic process -30.971072
GO:0009617 response to bacterium -30.378373
GO:0009625 response to insect -28.274766
GO:0009962 regulation of flavonoid biosynthetic process -26.178401
GO:1902025 nitrate import -25.374712
GO:0006468 protein phosphorylation -24.191598
GO:0006885 regulation of pH -22.650684
GO:0016567 protein ubiquitination -21.202896
GO:0010618 aerenchyma formation -20.939035
GO:0045168 cell-cell signaling involved in cell fate commitment -20.741224
GO:2000083 negative regulation of L-ascorbic acid biosynthetic process -19.412123
GO:0052544 defense response by callose deposition in cell wall -19.328769
GO:0000304 response to singlet oxygen -18.377153
GO:0071368 cellular response to cytokinin stimulus -17.273014
GO:0010942 positive regulation of cell death -17.144027
GO:0045926 negative regulation of growth -16.377114
GO:0060307 regulation of ventricular cardiac muscle cell membrane repolarization -16.205538
GO:0036371 protein localization to T-tubule -15.926428
GO:0033292 T-tubule organization -15.926428
GO:0036309 protein localization to M-band -15.926428
GO:0009626 plant-type hypersensitive response -14.583158
GO:0097185 cellular response to azide -14.343333
GO:0042742 defense response to bacterium -13.882315
GO:0010221 negative regulation of vernalization response -13.803582
GO:0071236 cellular response to antibiotic -13.743687
GO:0080027 response to herbivore -13.619727
GO:0009684 indoleacetic acid biosynthetic process -13.081209
GO:0080184 response to phenylpropanoid -13.076249
GO:0071466 cellular response to xenobiotic stimulus -12.698581
GO:0009871 jasmonic acid and ethylene-dependent systemic resistance,ethylene mediated signaling pathway -12.202141
GO:0009852 auxin catabolic process -11.640637
GO:0071766 Actinobacterium-type cell wall biogenesis -10.345361
GO:1904526 regulation of microtubule binding -10.149911
GO:0007166 cell surface receptor signaling pathway -9.953746
GO:0009664 plant-type cell wall organization -9.860266
GO:0009410 response to xenobiotic stimulus -9.553255
GO:1905255 regulation of RNA binding transcription factor activity -9.287265
GO:0009611 response to wounding -9.230396
GO:0006812 cation transport -9.129461
GO:0035864 response to potassium ion -9.109644
GO:0035024 negative regulation of Rho protein signal transduction -8.828881
GO:0009914 hormone transport -8.779619
GO:0010930 negative regulation of auxin mediated signaling pathway -8.668738
GO:0002213 defense response to insect -8.487227
GO:0070301 cellular response to hydrogen peroxide -8.171564
GO:0002011 morphogenesis of an epithelial sheet -7.878900
GO:0016045 detection of bacterium -7.717775
GO:0009867 jasmonic acid mediated signaling pathway -7.653627
GO:0010030 positive regulation of seed germination -7.578147
GO:1902265 abscisic acid homeostasis -7.314592
GO:0097237 cellular response to toxic substance -7.307836
GO:0034394 protein localization to cell surface -6.492217
GO:0009865 pollen tube adhesion -6.195394
GO:0090559 regulation of membrane permeability -6.056007
GO:0009866 induced systemic resistance,ethylene mediated signaling pathway -5.830010
GO:0007584 response to nutrient -5.725940
GO:0097167 circadian regulation of translation -5.676615
GO:0010233 phloem transport -5.653153
GO:0010310 regulation of hydrogen peroxide metabolic process -5.598483
GO:0009734 auxin-activated signaling pathway -5.404943
GO:0006355 regulation of transcription,DNA-templated -5.400441
GO:0003283 atrial septum development -5.212993
GO:0007267 cell-cell signaling -4.968237
GO:0009311 oligosaccharide metabolic process -4.824079
GO:0071218 cellular response to misfolded protein -4.715785
GO:0009826 unidimensional cell growth -4.518894
GO:0010114 response to red light -4.414258
GO:0061157 mRNA destabilization -4.339507
GO:0090305 nucleic acid phosphodiester bond hydrolysis -4.140630
GO:0009737 response to abscisic acid -4.079591
GO:0010438 cellular response to sulfur starvation -4.051106
GO:0015708 silicic acid import across plasma membrane -3.872000
GO:0031542 positive regulation of anthocyanin biosynthetic process -3.796297
GO:0006335 DNA replication-dependent chromatin assembly -3.727013
GO:0006649 phospholipid transfer to membrane -3.727013
GO:0009745 sucrose mediated signaling -3.704952
GO:0010305 leaf vascular tissue pattern formation -3.692859
GO:0002239 response to oomycetes -3.690236
GO:0032504 multicellular organism reproduction -3.668449
GO:0035600 tRNA methylthiolation -3.572083
GO:0009733 response to auxin -3.442921
GO:0009862 systemic acquired resistance,salicylic acid mediated signaling pathway -3.278010
GO:1905614 negative regulation of developmental vegetative growth -3.277570
GO:0032527 protein exit from endoplasmic reticulum -3.179807
GO:0051513 regulation of monopolar cell growth -3.105686
GO:1902290 positive regulation of defense response to oomycetes -3.039407
GO:0019722 calcium-mediated signaling -3.002484
GO:0097503 sialylation -3.001917
GO:0002230 positive regulation of defense response to virus by host -2.947989
GO:0006898 receptor-mediated endocytosis -2.859172
GO:0060359 response to ammonium ion -2.849739
GO:0071229 cellular response to acid chemical -2.672898
GO:0009960 endosperm development -2.621559
GO:0042177 negative regulation of protein catabolic process -2.592582
GO:1903522 regulation of blood circulation -2.582459
GO:0031640 killing of cells of other organism -2.578961
GO:1903553 positive regulation of extracellular exosome assembly -2.578840
GO:0048265 response to pain -2.578840
GO:0044364 disruption of cells of other organism -2.578840
GO:0045314 regulation of compound eye photoreceptor development -2.572936
GO:0007398 ectoderm development -2.572936
GO:0045747 positive regulation of Notch signaling pathway -2.572936
GO:0043086 negative regulation of catalytic activity -2.503942
GO:0001101 response to acid chemical -2.501541
GO:2000027 regulation of animal organ morphogenesis -2.482356
GO:0031347 regulation of defense response -2.473397
GO:0048821 erythrocyte development -2.466648
GO:0007498 mesoderm development -2.459655
GO:1905663 positive regulation of telomerase RNA reverse transcriptase activity -2.370150
GO:0010150 leaf senescence -2.119221
GO:1900865 chloroplast RNA modification -2.091400
GO:0009828 plant-type cell wall loosening -2.053815
GO:0010275 NAD(P)H dehydrogenase complex assembly -2.017866
GO:0009627 systemic acquired resistance -1.937599
GO:1900745 positive regulation of p38MAPK cascade -1.821475
GO:0007275 multicellular organism development -1.693810
GO:0046482 para-aminobenzoic acid metabolic process -1.527738
GO:0031930 mitochondria-nucleus signaling pathway -1.511118
GO:0001824 blastocyst development -1.495695
GO:0006260 DNA replication -1.402672
GO:0071219 cellular response to molecule of bacterial origin -1.350293
[1] “GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv”
TermID Name Value
GO:0006278 RNA-dependent DNA biosynthetic process -180.916060
GO:0032197 transposition,RNA-mediated -175.316613
GO:0090501 RNA phosphodiester bond hydrolysis -160.989575
GO:0006508 proteolysis -72.416255
GO:0090305 nucleic acid phosphodiester bond hydrolysis -55.006996
GO:0009451 RNA modification -51.871677
GO:0044550 secondary metabolite biosynthetic process -23.892755
GO:0010726 positive regulation of hydrogen peroxide metabolic process -18.244993
GO:0080181 lateral root branching -14.606194
GO:0032350 regulation of hormone metabolic process -11.320614
GO:0051258 protein polymerization -10.767659
GO:0071395 cellular response to jasmonic acid stimulus -10.138487
GO:0016101 diterpenoid metabolic process -9.758264
GO:0010942 positive regulation of cell death -9.704042
GO:0044245 polysaccharide digestion -6.692450
GO:0016081 synaptic vesicle docking -6.692450
GO:0032260 response to jasmonic acid stimulus involved in jasmonic acid and ethylene-dependent systemic resistance -6.439823
GO:0051603 proteolysis involved in cellular protein catabolic process -6.039701
GO:0015695 organic cation transport -5.617644
GO:0048462 carpel formation -4.934992
GO:0010337 regulation of salicylic acid metabolic process -4.452476
GO:0072488 ammonium transmembrane transport -4.131855
GO:0045962 positive regulation of development,heterochronic -4.056345
GO:0040007 growth -3.522516
GO:1900049 regulation of histone exchange -3.227057
GO:0071289 cellular response to nickel ion -3.177715
GO:0015709 thiosulfate transport -3.177715
GO:0033259 plastid DNA replication -3.177715
GO:0006182 cGMP biosynthetic process -2.777287
GO:0006032 chitin catabolic process -2.777287
GO:0007165 signal transduction -2.454269
GO:0009629 response to gravity -2.417378
GO:0009694 jasmonic acid metabolic process -2.381020
GO:0043086 negative regulation of catalytic activity -2.306902
GO:0080021 response to benzoic acid -2.299520
GO:0072756 cellular response to paraquat -2.299520
GO:0071465 cellular response to desiccation -2.299520
GO:0034265 isopentenyl adenine biosynthetic process -2.299520
GO:0070562 regulation of vitamin D receptor signaling pathway -2.278555
GO:0030511 positive regulation of transforming growth factor beta receptor signaling pathway -2.278555
GO:0048385 regulation of retinoic acid receptor signaling pathway -2.278555
GO:0002229 defense response to oomycetes -2.187161
GO:0006012 galactose metabolic process -2.057857
GO:0010258 NADH dehydrogenase complex (plastoquinone) assembly -1.880093
GO:0051707 response to other organism -1.559465
GO:0034461 uropod retraction -1.484321
GO:0090284 positive regulation of protein glycosylation in Golgi -1.465553
GO:0042773 ATP synthesis coupled electron transport -1.424052
GO:0080143 regulation of amino acid export -1.421822
GO:0043153 entrainment of circadian clock by photoperiod -1.421822
GO:0015990 electron transport coupled proton transport -1.421822
GO:0008347 glial cell migration -1.366082
[1] “GO_results_genes_lost_P_australis_not_other_seagrasses.csv”
TermID Name Value
GO:0009451 RNA modification -89.911120
GO:0090305 nucleic acid phosphodiester bond hydrolysis -89.381091
GO:0006278 RNA-dependent DNA biosynthetic process -20.038600
GO:0032197 transposition,RNA-mediated -19.701475
GO:0090501 RNA phosphodiester bond hydrolysis -17.299422
GO:0051603 proteolysis involved in cellular protein catabolic process -10.112687
GO:0032260 response to jasmonic acid stimulus involved in jasmonic acid and ethylene-dependent systemic resistance -8.751969
GO:0016081 synaptic vesicle docking -8.178899
GO:0048462 carpel formation -6.173514
GO:0006508 proteolysis -5.348966
GO:0006885 regulation of pH -4.363572
GO:0080156 mitochondrial mRNA modification -4.352576
GO:0071602 phytosphingosine biosynthetic process -4.167583
GO:0009694 jasmonic acid metabolic process -3.855562
GO:0043086 negative regulation of catalytic activity -3.708144
GO:0030244 cellulose biosynthetic process -3.449424
GO:0019761 glucosinolate biosynthetic process -3.391467
GO:0018008 N-terminal peptidyl-glycine N-myristoylation -3.253926
GO:0010064 embryonic shoot morphogenesis -3.253926
GO:0016131 brassinosteroid metabolic process -3.208332
GO:1902184 negative regulation of shoot apical meristem development -3.165687
GO:0006812 cation transport -3.078937
GO:0042273 ribosomal large subunit biogenesis -2.363144
GO:0010500 transmitting tissue development -2.323910
GO:0050434 positive regulation of viral transcription -2.302352
GO:0071289 cellular response to nickel ion -2.302352
GO:0010208 pollen wall assembly -2.288990
GO:0042773 ATP synthesis coupled electron transport -2.166858
GO:0080143 regulation of amino acid export -2.163578
GO:0043153 entrainment of circadian clock by photoperiod -2.163578
GO:0015990 electron transport coupled proton transport -2.163578
GO:0046785 microtubule polymerization -1.922603
GO:0032461 positive regulation of protein oligomerization -1.861507
GO:0048658 anther wall tapetum development -1.861507
GO:0006446 regulation of translational initiation -1.783246
GO:0097480 establishment of synaptic vesicle localization -1.778068
GO:0018401 peptidyl-proline hydroxylation to 4-hydroxy-L-proline -1.716219
GO:0019471 4-hydroxyproline metabolic process -1.716219
GO:0090284 positive regulation of protein glycosylation in Golgi -1.640876
GO:0042407 cristae formation -1.635329
GO:1900140 regulation of seedling development -1.374861
GO:0052472 modulation by host of symbiont transcription -1.358014
GO:0010374 stomatal complex development -1.351927
[1] “GO_results_genes_lost_Z_marina_not_other_seagrasses.csv”
TermID Name Value
GO:0009083 branched-chain amino acid catabolic process -12.099651
GO:1902418 (+)-abscisic acid D-glucopyranosyl ester transmembrane transport -12.065236
GO:0098660 inorganic ion transmembrane transport -9.090653
GO:0015700 arsenite transport -8.216962
GO:1901684 arsenate ion transmembrane transport -7.927843
GO:0040007 growth -7.168854
GO:0090284 positive regulation of protein glycosylation in Golgi -6.355361
GO:0071669 plant-type cell wall organization or biogenesis -5.783306
GO:0007059 chromosome segregation -5.267361
GO:0043617 cellular response to sucrose starvation -4.682327
GO:0007018 microtubule-based movement -4.630782
GO:0009313 oligosaccharide catabolic process -4.522609
GO:0090303 positive regulation of wound healing -4.515170
GO:2000114 regulation of establishment of cell polarity -4.303925
GO:1902198 3-methylbut-2-enoyl-CoA(4-) metabolic process -3.727762
GO:1904211 membrane protein proteolysis involved in retrograde protein transport,ER to cytosol -3.727762
GO:0043007 maintenance of rDNA -3.677400
GO:1900400 regulation of iron ion import into cell by regulation of transcription from RNA polymerase II promoter -3.277240
GO:1901255 nucleotide-excision repair involved in interstrand cross-link repair -3.277240
GO:0032508 DNA duplex unwinding -3.131414
GO:0034260 negative regulation of GTPase activity -3.043832
GO:0010104 regulation of ethylene-activated signaling pathway -2.878893
GO:0030837 negative regulation of actin filament polymerization -2.774984
GO:0097502 mannosylation -2.734209
GO:1900153 positive regulation of nuclear-transcribed mRNA catabolic process,deadenylation-dependent decay -2.645697
GO:1900049 regulation of histone exchange -2.607858
GO:0097193 intrinsic apoptotic signaling pathway -2.601213
GO:0000913 preprophase band assembly -2.495797
GO:0016573 histone acetylation -2.305824
GO:0009556 microsporogenesis -2.080502
GO:0006075 (1->3)-beta-D-glucan biosynthetic process -1.868028
GO:0071329 cellular response to sucrose stimulus -1.827140
GO:0051289 protein homotetramerization -1.755497
GO:0009624 response to nematode -1.749373
GO:0106004 tRNA (guanine-N7)-methylation -1.563561
GO:1900000 regulation of anthocyanin catabolic process -1.563561
GO:0097242 amyloid-beta clearance -1.533347
GO:0010992 ubiquitin recycling -1.533347
GO:0008340 determination of adult lifespan -1.533347
GO:0010815 bradykinin catabolic process -1.533347
GO:0010208 pollen wall assembly -1.374147
GO:0035194 post-transcriptional gene silencing by RNA -1.312663
[1] “GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv”
TermID Name Value
GO:0051603 proteolysis involved in cellular protein catabolic process -9.343439
GO:0071482 cellular response to light stimulus -4.060248
GO:0080156 mitochondrial mRNA modification -3.977341
GO:0046785 microtubule polymerization -3.919147
GO:0006624 vacuolar protein processing -3.194610
GO:0006597 spermine biosynthetic process -3.169700
GO:1990019 protein storage vacuole organization -2.561493
GO:0030174 regulation of DNA-dependent DNA replication initiation -2.463341
GO:0042372 phylloquinone biosynthetic process -2.463341
GO:0046900 tetrahydrofolylpolyglutamate metabolic process -1.766281
GO:0070914 UV-damage excision repair -1.765542
GO:0071332 cellular response to fructose stimulus -1.444683
GO:0010157 response to chlorate -1.444683
[1] “GO_results_genes_only_P_australis_not_other_seagrasses.csv”
TermID Name Value
GO:0005983 starch catabolic process -2.055820
GO:0034721 histone H3-K4 demethylation,trimethyl-H3-K4-specific -1.884385
GO:0046686 response to cadmium ion -1.754551
GO:0071333 cellular response to glucose stimulus -1.582738
GO:0030174 regulation of DNA-dependent DNA replication initiation -1.307768
[1] “GO_results_genes_only_Z_marina_not_other_seagrasses.csv”
TermID Name Value
GO:0051603 proteolysis involved in cellular protein catabolic process -23.445501
GO:0046785 microtubule polymerization -13.774183
GO:0006624 vacuolar protein processing -9.895786
GO:1990019 protein storage vacuole organization -8.591400
GO:0080156 mitochondrial mRNA modification -7.414447
GO:0010157 response to chlorate -5.513515
GO:0048281 inflorescence morphogenesis -4.588824
GO:0032989 cellular component morphogenesis -4.508650
GO:0090156 cellular sphingolipid homeostasis -4.494330
GO:0010090 trichome morphogenesis -4.097280
GO:1901332 negative regulation of lateral root development -2.847257
GO:0006278 RNA-dependent DNA biosynthetic process -2.761258
GO:0032197 transposition,RNA-mediated -2.708915
GO:0010286 heat acclimation -2.016484
GO:0090709 regulation of timing of plant organ formation -1.857388
GO:0006537 glutamate biosynthetic process -1.818101
GO:0090305 nucleic acid phosphodiester bond hydrolysis -1.818070
GO:0048194 Golgi vesicle budding -1.775108
GO:0009408 response to heat -1.548177
GO:0045332 phospholipid translocation -1.546385
GO:0015770 sucrose transport -1.318982
[1] “GO_results_genes_only_Z_muelleri_not_other_seagrasses.csv”
TermID Name Value
GO:0090284 positive regulation of protein glycosylation in Golgi -5.506616
GO:0010222 stem vascular tissue pattern formation -5.047945
GO:0008347 glial cell migration -4.650340
GO:0090303 positive regulation of wound healing -4.387055
GO:0040007 growth -4.373448
GO:1900049 regulation of histone exchange -4.140205
GO:2000114 regulation of establishment of cell polarity -3.856587
GO:0043007 maintenance of rDNA -3.318770
GO:2001240 negative regulation of extrinsic apoptotic signaling pathway in absence of ligand -2.928272
GO:0046328 regulation of JNK cascade -2.672143
GO:0080119 ER body organization -2.146026
GO:0007030 Golgi organization -1.799156
GO:0034260 negative regulation of GTPase activity -1.793183
GO:0046459 short-chain fatty acid metabolic process -1.740640
GO:0006336 DNA replication-independent chromatin assembly -1.395115
[1] “GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv”
TermID Name Value
GO:0000398 mRNA splicing,via spliceosome -4.253477
GO:0010252 auxin homeostasis -2.136050
GO:0006886 intracellular protein transport -1.945293
GO:0006334 nucleosome assembly -1.443671

Let’s have a look at all of these plots. Manually zooming in leads to ggrepel reloading labels, so on the small scale a lot of these plots don’t have labels.

for(i in names(plot_list)) {
  file_name = paste('output/',  i, '.png', sep='')
  
  cowplot::save_plot(file_name, plot_list[[i]], base_height=6)
  
}
Warning: ggrepel: 1 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Let me also try and make some patchworks.

# For some reason with this plot the legends aren't correctly collected by patchwork, 
# so I need to manually turn one off
patchy <- (plot_list[["GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv"]] + theme(legend.position = "none")) /
  plot_list[["GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv"]] + plot_layout(guides = 'collect') + plot_annotation(tag_levels = 'A')
patchy
Warning: ggrepel: 2 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

save(plot_list, file = 'output/all_GO_plots.Rdata') # save so I can put them together later

cowplot::save_plot('output/GO_results_terrestrials_vs_union_aquatics_seagrasses.png', patchy, base_height=7)
Warning: ggrepel: 1 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

OK I’ll better make this figure for the seagrasses alone, it’s quite messy this way.

Seagrass-specific loss

Let’s check which GO terms overlap between the 4 seagrasses!

How many shared lost GO-terms are there?

a <- list(`P. australis` = results_list$GO_results_genes_lost_P_australis_not_other_seagrasses.csv$Name,
          `A. antarctica` = results_list$GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv$Name,
          `Z. marina` = results_list$GO_results_genes_lost_Z_marina_not_other_seagrasses.csv$Name,
          `Z. muelleri` = results_list$GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv$Name)

a_go_ids <- list(`P. australis` = results_list$GO_results_genes_lost_P_australis_not_other_seagrasses.csv$TermID,
          `A. antarctica` = results_list$GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv$TermID,
          `Z. marina` = results_list$GO_results_genes_lost_Z_marina_not_other_seagrasses.csv$TermID,
          `Z. muelleri` = results_list$GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv$TermID)
plot(venn(a), 
     quantities = TRUE,
     fill = rev(wes_palette("Zissou1", 15, type = 'continuous')),
    alpha = 0.5,
     labels = list(font = 4))

upset(fromList(a), order.by='freq', )

a_no_ara <- list(`P. australis` = results_list$missing_posi_vs_all_GO.txt$Name,
          `A. antarctica` = results_list$missing_amphi_vs_all_GO.txt$Name,
          `Z. marina` = results_list$missing_zmar_vs_all_GO.txt$Name,
          `Z. muelleri` = results_list$missing_zmuel_vs_all_GO.txt$Name)

What are the shared GO-terms in seagrasses, WITHOUT the Ara loss??

Reduce(union, a) %>% enframe() %>% writexl::write_xlsx('./output/Seagrasses_shared_lost_genes.xlsx')

What if we remove Posidonia?

b <- list(`A. antarctica` = results_list$missing_amphi_vs_all_GO.txt$Name,
          `Z. marina` = results_list$missing_zmar_vs_all_GO.txt$Name,
          `Z. muelleri` = results_list$missing_zmuel_vs_all_GO.txt$Name)
intersections <- Reduce(intersect, b)
intersections[grepl('ethylene', intersections)]
NULL

OK we need a big list of all GO-terms here - which GO-term is lost in which species. That will be a supplementary table.

all_species <- c("P. australis","A. antarctica","Z. marina","Z. muelleri", 'A. thaliana')  
all_go_terms <- Reduce(union, a)
all_go_ids <- Reduce(union, a_go_ids)
results_d <- data.frame('GOID' = character(),
                        'GO' = character(),
                        'P. australis' = character(),
                        'A. antarctica' = character(),
                        'Z. marina' = character(),
                        'Z. muelleri' = character(),
                        'A. thaliana' = character())


for (index in seq_along(all_go_terms)){
  go <- all_go_terms[index]
  go_id <- all_go_ids[index]
  specs <- c()
  for (species in names(a)) {
    if ( length(a[[species]][grep(paste('^', go, '$', sep=''), a[[species]])]) > 0 ) {
      specs <- c(specs, species)
    }
  }
  
  results_d[index,] <- c(go_id, go, gsub('FALSE', 'Present', gsub('TRUE', 'Lost', all_species %in% specs)))
}
writexl::write_xlsx(results_d, 'output/Lost_GO_terms_in_five_species.xlsx')

After filtering for plant-specific GO-terms

We will use the GO-terms that are plant-specific as identified by the GOMAP paper. See https://github.com/wkpalan/GOMAP-maize-analysis/blob/main/6.plantSpecific/1.getSppSpecific.R or https://plantmethods.biomedcentral.com/articles/10.1186/s13007-021-00754-1

go_plant <- read_tsv('https://raw.githubusercontent.com/wkpalan/GOMAP-maize-analysis/main/data/go/speciesSpecificGOTerms.txt')
Rows: 45031 Columns: 5
-- Column specification --------------------------------------------------------
Delimiter: "\t"
chr (1): GOterm
dbl (4): NCBITaxon:10090, NCBITaxon:33090, NCBITaxon:3702, NCBITaxon:40674

i Use `spec()` to retrieve the full column specification for this data.
i Specify the column types or set `show_col_types = FALSE` to quiet this message.
# taxon 33090 is Viridiplantae
plantSpecificGO <- go_plant %>% dplyr::filter(`NCBITaxon:33090`==1) %>% pull(GOterm)
plantSpecificGO <- c(plantSpecificGO,c("GO:0005575","GO:0008150","GO:0003674"))
results_d %>% filter(GOID %in% plantSpecificGO) %>% writexl::write_xlsx('output/Lost_GO_terms_in_five_species.PlantSpecific.xlsx')

Now let’s redo the Venn diagram with those filtered GO-terms

filters <- lapply(a_go_ids, function(ch) ch %in% plantSpecificGO)

newa <- list()
for (species in names(filters)) {
  before <- a[[species]]
  after <- before[filters[[species]]]
  newa[[species]] <- after
}
plot(venn(newa), 
     quantities = TRUE,
     fill = rev(wes_palette("Zissou1", 15, type = 'continuous')),
    alpha = 0.5,
     labels = list(font = 4))

Not much difference?


sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale:
[1] LC_COLLATE=English_Australia.1252  LC_CTYPE=English_Australia.1252   
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C                      
[5] LC_TIME=English_Australia.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] patchwork_1.1.1      kableExtra_1.3.4     rrvgo_1.4.4         
 [4] UpSetR_1.4.0         eulerr_6.1.1         ggrepel_0.9.1       
 [7] stringi_1.7.5        httr_1.4.2           wesanderson_0.3.6   
[10] rvest_1.0.2          forcats_0.5.1        stringr_1.4.0       
[13] dplyr_1.0.7          purrr_0.3.4          readr_2.1.2         
[16] tidyr_1.1.4          tibble_3.1.5         ggplot2_3.3.5       
[19] tidyverse_1.3.1      topGO_2.44.0         SparseM_1.81        
[22] GO.db_3.13.0         AnnotationDbi_1.54.1 IRanges_2.26.0      
[25] S4Vectors_0.30.2     Biobase_2.52.0       graph_1.70.0        
[28] BiocGenerics_0.38.0  workflowr_1.6.2     

loaded via a namespace (and not attached):
  [1] colorspace_2.0-2       ellipsis_0.3.2         rprojroot_2.0.2       
  [4] XVector_0.32.0         fs_1.5.0               rstudioapi_0.13       
  [7] farver_2.1.0           bit64_4.0.5            fansi_0.5.0           
 [10] lubridate_1.8.0        xml2_1.3.2             cachem_1.0.6          
 [13] GOSemSim_2.18.1        knitr_1.36             polyclip_1.10-0       
 [16] jsonlite_1.7.2         broom_0.7.9            gridBase_0.4-7        
 [19] dbplyr_2.1.1           png_0.1-7              pheatmap_1.0.12       
 [22] shiny_1.7.1            compiler_4.1.0         backports_1.2.1       
 [25] assertthat_0.2.1       fastmap_1.1.0          cli_3.2.0             
 [28] later_1.3.0            htmltools_0.5.2        tools_4.1.0           
 [31] igraph_1.2.7           NLP_0.2-1              gtable_0.3.0          
 [34] glue_1.6.2             GenomeInfoDbData_1.2.6 Rcpp_1.0.7            
 [37] slam_0.1-48            cellranger_1.1.0       jquerylib_0.1.4       
 [40] vctrs_0.3.8            Biostrings_2.60.2      writexl_1.4.0         
 [43] svglite_2.1.0          polylabelr_0.2.0       xfun_0.27             
 [46] mime_0.12              lifecycle_1.0.1        zlibbioc_1.38.0       
 [49] scales_1.1.1           treemap_2.4-3          vroom_1.5.7           
 [52] hms_1.1.1              promises_1.2.0.1       RColorBrewer_1.1-2    
 [55] curl_4.3.2             yaml_2.2.1             memoise_2.0.0         
 [58] gridExtra_2.3          sass_0.4.0             RSQLite_2.2.8         
 [61] highr_0.9              GenomeInfoDb_1.28.4    systemfonts_1.0.4     
 [64] rlang_0.4.12           pkgconfig_2.0.3        matrixStats_0.61.0    
 [67] bitops_1.0-7           evaluate_0.14          lattice_0.20-44       
 [70] labeling_0.4.2         cowplot_1.1.1          bit_4.0.4             
 [73] tidyselect_1.1.1       plyr_1.8.6             magrittr_2.0.1        
 [76] R6_2.5.1               generics_0.1.1         DBI_1.1.1             
 [79] pillar_1.6.4           haven_2.4.3            whisker_0.4           
 [82] withr_2.5.0            KEGGREST_1.32.0        RCurl_1.98-1.5        
 [85] modelr_0.1.8           crayon_1.4.1           wordcloud_2.6         
 [88] utf8_1.2.2             tzdb_0.1.2             rmarkdown_2.11        
 [91] grid_4.1.0             readxl_1.3.1           data.table_1.14.2     
 [94] blob_1.2.2             git2r_0.28.0           webshot_0.5.2         
 [97] reprex_2.0.1           digest_0.6.28          xtable_1.8-4          
[100] tm_0.7-8               httpuv_1.6.3           munsell_0.5.0         
[103] viridisLite_0.4.0      bslib_0.3.1