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Here I compare read alignment differences with known Arabidopsis genes.

library(tidyverse)
Warning: package 'tidyverse' was built under R version 4.1.1
-- Attaching packages --------------------------------------- tidyverse 1.3.1 --
v ggplot2 3.3.5     v purrr   0.3.4
v tibble  3.1.5     v dplyr   1.0.7
v tidyr   1.1.4     v stringr 1.4.0
v readr   2.0.2     v forcats 0.5.1
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 4.1.1
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
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
library(cowplot)
Warning: package 'cowplot' was built under R version 4.1.1
theme_set(theme_cowplot())
library(RColorBrewer)
Warning: package 'RColorBrewer' was built under R version 4.1.1
library(wesanderson)
Warning: package 'wesanderson' was built under R version 4.1.1
library(gghighlight)
Warning: package 'gghighlight' was built under R version 4.1.2
library(patchwork)
Warning: package 'patchwork' was built under R version 4.1.1

Attaching package: 'patchwork'
The following object is masked from 'package:cowplot':

    align_plots
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())

The data is based on Supplementary Table S6 and S7.

Stomata genes

stomata <- tibble::tribble(
             ~Gene.symbol, ~A..antarctica, ~P..australis, ~H..ovalis, ~Z..muelleri, ~Z..marina,
                 "SBT1.2",              0,             0,                  5.63,          8.2,       4.34,
                  "EPFL9",              0,             0,                     0,            0,          0,
                   "EPF1",              0,         25.08,                     0,            0,          0,
                    "TMM",           3.35,             0,                     0,            0,          0,
                   "EPF2",              0,             0,                     0,            0,          0,
                  "MYB88",              0,             0,                  6.74,         2.34,          0,
                   "MUTE",              0,             0,                     0,            0,          0,
                   "SPCH",           7.95,          3.29,                  5.84,         4.47,          0,
                   "FAMA",           6.99,         20.64,                  6.83,         4.98,       4.98,
                  "SCRM2",           21.8,         25.57,                 19.66,        26.16,      22.25,
                    "FLP",            3.2,          8.77,                  4.42,            0,          0
             )
stomata_long <- stomata %>% pivot_longer(-Gene.symbol, values_to = 'Coverage', names_to='Species') %>% 
  mutate(Species = gsub('\\.\\.', '. ', Species)) %>% 
  filter(Species != 'H. ovalis')
stom_p <- stomata_long %>% ggplot(aes(x=forcats::fct_rev(Species), y=Coverage, fill=Species, color=Species)) + 
  geom_boxplot(
    aes(fill = after_scale(colorspace::lighten(fill, .9))),
    size = 1.5, outlier.shape = NA
  ) +
  geom_jitter(width = .1, size = 4, alpha = .5) +
  ylim(c(-1,100)) +
  
  theme(legend.position = "None",
  axis.text.y = element_text(face = "italic")) +
  scale_color_brewer(palette='Dark2') +
  ylab('Coverage (%)') +
  coord_flip() + xlab('Species')

stom_p

label <- stomata_long #%>% mutate(Gene.symbol = stringr::str_to_lower(Gene.symbol)) 
label <- label %>% 
  mutate(mylabel = case_when(Coverage >= 100 ~ '',
                             Coverage == 0 ~ '',
                                    TRUE ~ as.character(Coverage)))


stom_heat <- stomata_long %>% 
  #mutate(Gene.symbol = stringr::str_to_lower(Gene.symbol)) %>% 
  ggplot(aes(x=Species, y=factor(Gene.symbol, level=rev(unique(Gene.symbol))), fill=Coverage)) + 
  geom_tile(alpha=0.9, color='white') + 
  geom_text(aes(label=mylabel), data=label, size=3.5) + 
  theme(axis.text.y = element_text(face = "italic"),
        axis.text.x = element_text(face='italic'),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        legend.position = "none") +
  scale_fill_continuous(limits=c(0,100))

stom_heat

Ethylene

ethylene <- tibble::tribble(
              ~Gene.symbol, ~A..antarctica, ~P..australis, ~H..ovalis, ~Z..muelleri, ~Z..marina,
                    "ACO1",              0,         53.16,          0,            0,          0,
                    "ACO2",              0,         11.53,          0,            0,          0,
                    "ACO4",              0,         15.74,          0,            0,          0,
                    "ACO5",              0,             0,          0,         6.39,        5.3,
                    "ACS1",           9.34,          5.11,          0,            0,          0,
                    "ACS2",           7.24,          5.97,          0,         4.43,          0,
                    "ACS4",          18.74,         25.19,          0,         8.49,       8.21,
                    "ACS5",          19.25,         50.39,       4.46,            0,          0,
                    "ACS6",              0,             0,          0,            0,          0,
                    "ACS7",          10.27,         66.29,          0,         6.47,          0,
                    "ACS8",          38.58,         42.62,       6.24,            0,          0,
                    "ACS9",          20.52,         36.94,          0,            0,          0,
                   "ACS11",              0,         22.05,       7.45,            0,          0,
                    "ERS1",          35.23,         40.88,          0,          2.5,          0,
               "ETR1/EIN1",          49.57,         51.87,          0,         3.83,          0,
                    "ETR2",              0,         21.96,          0,            0,          0,
                    "EIN4",           1.74,         31.33,          0,            0,       1.78,
                    "CTR1",          26.68,         31.55,       5.96,            0,          0,
                    "EIN2",              0,         14.54,      11.12,            0,          0,
                    "EBF1",              0,             0,        4.5,            0,          0,
                    "EBF2",              0,         12.45,       4.22,            0,          0,
                    "EIN3",          27.03,         43.08,      36.83,        31.27,      31.11,
                    "MYC2",           4.43,         27.83,      10.31,        23.61,       23.5,
                    "MYC3",             19,         17.14,      10.06,        12.14,      13.77,
                    "MYC4",              0,          3.84,       8.19,        20.96,      11.75
              )
ethylene_long <- ethylene %>% pivot_longer(-Gene.symbol, values_to = 'Coverage', names_to='Species') %>% 
  mutate(Species = gsub('\\.\\.', '. ', Species)) %>% 
  filter(Species != 'H. ovalis')
eth_p <- ethylene_long %>% ggplot(aes(x=forcats::fct_rev(Species), y=Coverage, fill=Species, color=Species)) + 
  geom_boxplot(
    aes(fill = after_scale(colorspace::lighten(fill, .9))),
    size = 1.5, outlier.shape = NA
  ) +
  geom_jitter(width = .1, size = 4, alpha = .5) +
  ylim(c(-1,100)) +
  
  theme(legend.position = "None",
  axis.text.y = element_text(face = "italic")) +
  scale_color_brewer(palette='Dark2') +
  ylab('Coverage (%)') +
  coord_flip() +
  xlab('Species')
eth_p

eth_heat <- ethylene_long %>% 
  dplyr::filter(Gene.symbol != 'ndhB-2') %>% 
  mutate(Gene.symbol = stringr::str_to_lower(Gene.symbol)) %>% 
  ggplot(aes(x=Species, y=factor(Gene.symbol, level=rev(unique(Gene.symbol))), fill=Coverage)) + 
  geom_tile() + 
  ylab('Gene') +
  theme(axis.text.y = element_text(face = "italic"),
        axis.text.x = element_text(face='italic')) +
  scale_fill_continuous(limits=c(0,100))

eth_heat

NDH genes

ndh <- tibble::tribble(
         ~Gene.symbol, ~A..antarctica, ~P..australis, ~H..ovalis, ~Z..muelleri, ~Z..marina,
               "NDHL",              0,             0,          0,        16.67,      16.67,
               "NDHM",              0,             0,          0,        36.24,       34.4,
               "NDHN",          48.73,             0,          0,        66.35,      59.68,
               "NDHO",              0,             0,          0,        33.54,      22.22,
               "NDHS",          12.35,         28.29,          0,         34.4,      30.15,
               "NDHT",              0,          8.67,          0,        19.47,      16.67,
               "NDHU",              0,             0,          0,         9.89,          0,
              "PNSB1",           4.26,         42.42,          0,         32.4,      31.24,
              "PNSB2",              0,             0,          0,            0,          0,
              "PNSB3",              0,          8.46,          0,        16.26,       9.76,
              "PNSB4",              0,         19.13,          0,        18.75,      18.75,
              "PNSL1",              0,             0,          0,            0,          0,
              "PNSL2",          16.58,             0,          0,        45.03,      15.01,
              "PNSL3",              0,             0,          0,            0,          0,
              "PNSL4",           7.19,         23.55,          0,        31.04,      45.11,
              "PNSL5",          52.82,         62.82,      57.31,        48.72,      46.28,
               "CRR6",              0,             0,          0,        43.86,      33.06,
               "CRR7",              0,             0,          0,            0,          0,
              "Lhca5",              0,         35.15,          0,        18.29,      27.76,
              "Lhca6",              0,         47.85,          0,        58.43,      60.27,
              "CRR27",           21.9,           9.2,       9.26,        36.38,      41.78,
              "CRR41",              0,             0,          0,        44.03,       7.86,
               "PGR5",          55.97,         56.72,      53.98,        55.22,      55.22,
             "PGRL1A",          17.54,         23.79,      29.54,        33.54,      31.08,
               "CRR2",          41.49,          61.4,       2.94,        23.51,      13.93,
               "CRR3",              0,             0,          0,            0,          0,
              "CRR42",              0,             0,          0,        30.89,      28.44,
               "PQL3",              0,             0,          0,            0,          0,
               "NDF5",              0,             0,          0,            0,          0
         )
ndh_long <- ndh %>% pivot_longer(-Gene.symbol, values_to = 'Coverage', names_to='Species') %>% 
  mutate(Species = gsub('\\.\\.', '. ', Species)) %>% 
  filter(Species != 'H. ovalis')
ndh_p <- ndh_long %>% ggplot(aes(x=forcats::fct_rev(Species), y=Coverage, fill=Species, color=Species)) + 
  geom_boxplot(
    aes( fill = after_scale(colorspace::lighten(fill, .9))),
    size = 1.5, outlier.shape = NA
  ) +
  geom_jitter(width = .1, size = 4, alpha = .5) +
  ylim(c(-1,100)) +
  
  theme(legend.position = "None",
  axis.text.y = element_text(face = "italic")) +
  scale_color_brewer(palette='Dark2') +
  ylab('Coverage %') +
  coord_flip() +
  xlab('Species')
ndh_p

label <- ndh_long
label <- label %>% 
  mutate(mylabel = case_when(Coverage >= 100 ~ '',
                             Coverage == 0 ~ '',
                                    TRUE ~ as.character(Coverage)))


ndh_heat <- ndh_long %>% 
  dplyr::filter(Gene.symbol != 'ndhB-2') %>% 
  mutate(Gene.symbol = stringr::str_to_lower(Gene.symbol)) %>% 
  ggplot(aes(x=Species, y=factor(Gene.symbol, level=rev(unique(Gene.symbol))), fill=Coverage)) + 
  geom_tile() + 
  geom_tile(alpha=0.9, color='white') + 
  #geom_text(data=label, aes(label=mylabel), size=3.5) +
  theme(axis.text.y = element_text(face = "italic"),
        axis.text.x = element_text(face = 'italic'),
        axis.title.x = element_blank(),
        axis.title.y = element_blank())  +
  scale_fill_continuous(limits=c(0,100))

ndh_heat

The following data is slightly different because it compares lengths of annotated genes in the chloroplast assembly.

ndh_chloro <- tibble::tribble(
  ~Gene.symbol, ~A..antarctica, ~H..ovalis, ~P..australis, ~Z..marina, ~Z..muelleri,
        "ndhA",              0,          0,             0,      101.8,        101.4,
        "ndhB",              0,          0,             0,      100.4,        100.9,
      "ndhB-2",              0,          0,             0,      100.4,        100.9,
        "ndhC",           92.5,          0,           100,        100,          100,
        "ndhD",           29.4,          0,             0,        100,          100,
        "ndhE",              0,          0,          45.4,        100,          100,
        "ndhF",              0,          0,             0,       98.4,         98.3,
        "ndhG",           45.9,          0,             0,        100,          100,
        "ndhH",             34,       63.1,          63.8,        100,          100,
        "ndhI",              0,          0,             0,      110.5,        110.5,
        "ndhJ",           70.8,          0,             0,        100,          100,
        "ndhK",             55,          0,         109.3,      109.8,        109.8
  )
ndh_chl_long <- ndh_chloro %>% pivot_longer(-Gene.symbol, values_to = 'Coverage', names_to='Species') %>% 
  mutate(Species = gsub('\\.\\.', '. ', Species)) %>% 
  filter(Species != 'H. ovalis')

Stylistic choice - if the new gene is longer than the Arabidopsis one, set to 100%.

ndh_chl_p <- ndh_chl_long %>%
  mutate(Coverage = case_when(Coverage > 100 ~ 100,
                              TRUE ~ Coverage)) %>% 
  ggplot(aes(x=forcats::fct_rev(Species), y=Coverage, fill=Species, color=Species)) + 
  geom_boxplot(
    aes( fill = after_scale(colorspace::lighten(fill, .9))),
    size = 1.5, outlier.shape = NA
  ) +
  geom_jitter(width = .1, size = 4, alpha = .5) +
  ylim(c(-1,100.1)) +
  
  theme(legend.position = "None",
  axis.text.y = element_text(face = "italic")) +
  scale_color_brewer(palette='Dark2') +
  ylab('Gene size similarity (%)') +
  xlab('Species') +
  coord_flip()
ndh_chl_p

label <- ndh_chl_long %>% filter(Gene.symbol != 'ndhB-2')
label <- label %>% 
  mutate(mylabel = case_when(Coverage >= 100 ~ '',
                             Coverage == 0 ~ '',
                                    TRUE ~ as.character(Coverage)))

ndh_chl_heat <- ndh_chl_long %>% 
  dplyr::filter(Gene.symbol != 'ndhB-2') %>% 
  mutate(Coverage = case_when(Coverage > 100 ~ 100,
                              TRUE ~ Coverage)) %>% 
  ggplot(aes(x=Species, y=factor(Gene.symbol, level=rev(unique(Gene.symbol))), fill=Coverage)) + 
  geom_tile(alpha=0.9, color='white') + 
  geom_text(data=label, aes(label=mylabel), size=3.5) +
  ylab('Gene') +
  theme(axis.text.y = element_text(face = "italic"),
        axis.text.x = element_text(face = 'italic'),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        legend.position = "none") +
  scale_fill_continuous(limits=c(0,100))
  
ndh_chl_heat

all together

patchwork <- (eth_p + stom_p) / ( ndh_chl_p + ndh_p )
# patchwork[[2]] = patchwork[[2]] + theme(axis.text.y = element_blank(),
#                                         axis.ticks.y = element_blank(),
#                                         axis.title.y = element_blank() )
# patchwork[[1]] = patchwork[[1]] + theme(axis.text.y = element_blank(),
#                                         axis.ticks.y = element_blank(),
#                                         axis.title.y = element_blank() )
patchwork+ plot_annotation(tag_levels = "A")

patchwork <- (eth_p + ndh_chl_heat)/
 (ndh_p + stom_heat  )
#patchwork[[2]] = patchwork[[2]] + theme(axis.title.x = element_blank() )
#patchwork[[1]] = patchwork[[1]] + theme(axis.title.x = element_blank() )
puh <- patchwork+ plot_annotation(tag_levels = "A") #+ plot_layout(guides='none')
puh

cowplot::save_plot(filename = 'output/patched_gene_loss.png', plot = puh, base_height = 7)

Hmmmmmmmmm


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] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] patchwork_1.1.1    gghighlight_0.3.2  wesanderson_0.3.6  RColorBrewer_1.1-2
 [5] cowplot_1.1.1      forcats_0.5.1      stringr_1.4.0      dplyr_1.0.7       
 [9] purrr_0.3.4        readr_2.0.2        tidyr_1.1.4        tibble_3.1.5      
[13] ggplot2_3.3.5      tidyverse_1.3.1    workflowr_1.6.2   

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.7       lubridate_1.8.0  assertthat_0.2.1 rprojroot_2.0.2 
 [5] digest_0.6.28    utf8_1.2.2       R6_2.5.1         cellranger_1.1.0
 [9] backports_1.2.1  reprex_2.0.1     evaluate_0.14    highr_0.9       
[13] httr_1.4.2       pillar_1.6.4     rlang_0.4.12     readxl_1.3.1    
[17] rstudioapi_0.13  whisker_0.4      jquerylib_0.1.4  rmarkdown_2.11  
[21] labeling_0.4.2   munsell_0.5.0    broom_0.7.9      compiler_4.1.0  
[25] httpuv_1.6.3     modelr_0.1.8     xfun_0.27        pkgconfig_2.0.3 
[29] htmltools_0.5.2  tidyselect_1.1.1 fansi_0.5.0      crayon_1.4.1    
[33] tzdb_0.1.2       dbplyr_2.1.1     withr_2.4.2      later_1.3.0     
[37] grid_4.1.0       jsonlite_1.7.2   gtable_0.3.0     lifecycle_1.0.1 
[41] DBI_1.1.1        git2r_0.28.0     magrittr_2.0.1   scales_1.1.1    
[45] cli_3.0.1        stringi_1.7.5    farver_2.1.0     fs_1.5.0        
[49] promises_1.2.0.1 xml2_1.3.2       bslib_0.3.1      ellipsis_0.3.2  
[53] generics_0.1.1   vctrs_0.3.8      tools_4.1.0      glue_1.4.2      
[57] hms_1.1.1        fastmap_1.1.0    yaml_2.2.1       colorspace_2.0-2
[61] rvest_1.0.2      knitr_1.36       haven_2.4.3      sass_0.4.0