Taxonomy | Miao Sun | 孙苗

How to built a completely resolved species-level phylogeny using TCAT

Sun, 06 Sep 2020 00:00:00 +0000

Phylogenetic tree is a crucial reference system for biological research. It carries the key information for species diversification through geological time. A phylogeny tree with all members of a lineage presented is necessary for questions in macroecology and macroevolution. Hence, there are many comparative biological methods (e.g., diversification) integreated “sampling fractions” or other approches to correct sparsely sampled phylogenies of higher taxonomic groups. For example, “sampling fractions” in RPANDA (Morlon et al. 2016) and “global sampling fraction” and “clade-specific sampling fraction” in BAMM (Rabosky, 2014; Sun et al., 2020). However, this approach could lead to low statistical power to infer rate variation, or spurious patterns of diversification, which may further impact the evolutionary implication (Chang et al., 2019).
A new stochastic polytomy resolution method — Taxonomic Addition for Complete Trees (TACT) is able to avoid the biases arised above, and also can greatly improve the power of estimation in diversification analyses (Chang et al., 2019). It uses birth–death-sampling model and taxonomic information to place unsampled taxa onto the ultrametric target backbone phylogeny. It produces a pseduposterior distribution of phylogenies, integrating diversification rates with phylogenetic uncertainty and speciation times, while this approach also can be labor and computation time intense as well as require topology constraint. Besides TACT, other stochastic polytomy resolvers, including PASTIS (Thomas et al., 2013) and CorSiM (Cusimano et al., 2012), but TACT performes better (See Chang et al., 2019).

The caveats which researchers should pay attention is that complete phylogenies generared by stochastic polytomy resolvers should NOT be used for estimating the trait evolution. Because the way of how complete tree is generated, the true rate of trait evolution can be overestimated, and the phylogenetic signal is lost.

The Author Jonathan Chang already has a detailed tutorial of how to install and run TACT. Here I only focus on how to prepare a taxonomy list and built up pipeline for my own project.

General steps

First thing first, you need two files to run TACT (assuming that you have successfully installed TACT and its dependencies):

An ultrametric backbone phylogeny (e.g., Vitales_dated.tre)
A taxonomy of target clade

this can be taxonomy tree (see Chang et al., 2019)
can also be a taxonomic list in csv format with all taxonomic ranks listed (e.g., genus, family, order; here as Vitales.csv)

For the case in my post, I use Vitales as an example. The Vitales taxonomic list is generated from WCSP website, and the higher taxonomic ranks are queried from APWeb. The backbone tree was built using RAxML with molecular data mined from GenBank via PyPHLAWD, and then dated using treePL.

1. Prepare a taxonomic list

A csv format
All taxonomic ranks referenced from APWeb
Columns layout as order,family,genus,genus.species

# devtools::install_github("wcornwell/taxonlookup")
rm(list=ls())
library("taxonlookup")
library("ape")
library("dplyr", warn.conflicts = FALSE, quietly = TRUE)
#read in the complete taxonomic list
Vitales <- read.csv("Vitales_rawlist.csv", header = T, stringsAsFactors = F)
# > head(Vitales)
# [1] "Acareosperma spireanum"
# [2] "Ampelocissus abyssinica"
# [3] "Ampelocissus acapulcensis"
# [4] "Ampelocissus acetosa"
# [5] "Ampelocissus aculeata"
# [6] "Ampelocissus africana var. migeodii"
# lookup APGWeb based on species names
Vitales.apg <- lookup_table(unique(Vitales), missing_action = "NA", by_species=TRUE)
#just manual check if there are some genera are failed to have query
if(sum(is.na(Vitales.apg$family)) >0){
tt <- Vitales.apg[is.na(Vitales.apg$family),]
print(tt)
}
# rearrange columns as taxonomic ranks
APG_table <- Vitales.apg %>% mutate(genus.species=row.names(Vitales.apg)) %>% select(order, family, genus, genus.species)
#
#> head(APG_table)
#order family genus genus.species
#1 Vitales Vitaceae Acareosperma Acareosperma spireanum
#2 Vitales Vitaceae Ampelocissus Ampelocissus abyssinica
#3 Vitales Vitaceae Ampelocissus Ampelocissus acapulcensis
#4 Vitales Vitaceae Ampelocissus Ampelocissus acetosa
#5 Vitales Vitaceae Ampelocissus Ampelocissus aculeata
#6 Vitales Vitaceae Ampelocissus Ampelocissus africana var. migeodii
#replace space as underscore
APG_table$genus.species <- gsub(" ", "_",APG_table$genus.species)
#save the apg lookup table, and prepare for next step TACT
write.csv(APG_table, "Vitales.csv", row.names=FALSE, quote=FALSE)

2. Run TACT

#Build a taxonomic tree
tact_build_taxonomic_tree Vitales.csv --output Vitales.taxonomy.tre
# this step adove can be skipped, if you already have a taxonomy tree
#Run the TACT stochastic polytomy resolver algorithm in conjunction with the backbone phylogeny
tact_add_taxa --backbone Vitales_dated.tre --taxonomy Vitales.taxonomy.tre --output Vitales.tacted --verbose
#check the TACT results
tact_check_results Vitales.tacted.newick.tre --backbone Vitales_dated.tre --taxonomy Vitales.taxonomy.tre > Vitales_checkresults.csv

3. Visualize and compare trees

library("ape")
tree1 <- ladderize(read.tree("./Vitales_dated.tre"))
plot.phylo(tree1, cex=0.1, type = "fan", main="Backbone tree with NCBI data")

This is the original backbone tree before TACT treatment

Vitales backbone

Now we show which tips on the complete species-level tree are added by TACT:

tree2 <- ladderize(read.tree("./Vitales.tacted.newick.tre"))
tip.cl <- ifelse(tree2$tip.label %in% tree1$tip.label, "black", "red")
plot.phylo(tree2, tip.color=tip.cl, cex=0.1, type = "fan", main="complete tree with NCBI + Taxonomic data")
mtext("Red tips are species added by TACT", col = "red", side=1, line=-5, outer=TRUE)

Vitales Tacted Tree1

Last, We highlight which tree edges on the complete species-level tree are added by TACT:

library("phytools")
x <- setNames(ifelse(tree2$tip.label %in% tree1$tip.label, "0", "1"), tree2$tip.label)
a <- names(x)[x=="0"]
b <- names(x)[x=="1"]
tt<-paintBranches(tree2,edge=sapply(b,match,tree2$tip.label),
state="b",anc.state="a")
cols<-setNames(c("black","red"),c("a","b"))
plot(tt, colors=cols, fsize=0.1, type="fan", lwd=0.5)
mtext("Red branches are imputated by TACT", col = "red", side=3, line=-1.5, outer=TRUE)

Vitales Tacted Tree2

That’s it.

Reference

Thomas G.H. et al. PASTIS: an R package to facilitate phylogenetic assembly with soft taxonomic inferences. Methods Ecol. Evol. 4:1011–1017 (2013).
Chang et al. Estimating Diversification Rates on Incompletely Sampled Phylogenies: Theoretical Concerns and Practical Solutions. Syst. Biol. 69(3):602–611, 2020
Cusimano N.et al. A new method for handling missing species in diversification analysis applicable to randomly or nonrandomly sampled phylogenies. Syst. Biol. 61:785–792 (2012).
Morlon, H. et al. RPANDA: an R package for macroevolutionary analyses on phylogenetic trees. Methods Ecol. Evol. 7, 589–597 (2016).
Rabosky, D. L. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. PLoS ONE 9, e89543 (2014).
Revell, J. L. Phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
Sun, M. et al. Estimating rates and patterns of diversification with incomplete sampling: A case study in the rosids. Am. J. Bot. 107, 1–15 (2020).

Field work activities from 2006-2012 in China

Sun, 13 Jan 2019 00:00:00 +0000

I have visited a lot places in south part of China. These places are genreally hostspots of biodiversity of China. Especially I love Xizang! I hope I have chance to introduce more details of this facinating landscape, spelendid vegation, and each plant I came across during my trip.

🍀 🌸 🌿 🌵 🍄 🌴 🌳 🌼

Here some bullets of my trips I have make since 2006 - 2012:

2012
Trip to southern Yunnan along Myanmar border with Pam S. Soltis and Doug E. Soltis, collecting materials for Tree of life — China Project. Trip to Hainan tropical rain forest with Doug E. Soltis, collecting materials of Tree for life — China Project.
2006 ~ 2011
Joined in the expedition team of national herbarium (PE) for collection many times, successively visited a series of biodiversity hotspots, such as Jilin, Hubei, Chongqing, Guangxi, Sichuan, Xizang, etc.

I use R code and Baidumap API to show my trips:

Warning: This script may not work well in R markdown enviroment, but I tried by copying out the code as a single script in R studio. It works.

rm(list=ls())
# you need to install these packages if have not done so.
#install.packages("devtools")
# devtools::install_github("lchiffon/REmap")
# devtools::install_github("badbye/baidumap"")
install.packages("png")
library("png")
library("REmap")
library("baidumap")
# I realized chinese string have more success match with their coordinates
city<- c("北京","吉林省", "广东","湖北","重庆","广西","西藏","四川", "云南", "海南")
begin<-rep("beijing",length(city)) #(起点)
mapdata<-data.frame(begin,city)
getBaiduMap2(city, width = 400, height = 400, zoom = 10, scale = 2,
color = "color", messaging = TRUE)
map_pic <- remap(mapdata = mapdata, #数据框
title = "Footsteps covered most hotspots of China", #标题
subtitle = "Field work activities from 2006-2012", #副标题
theme = get_theme(theme = "Dark")) #主题
plot(map_pic)

Field trip trail

Taxonomy

Mon, 10 Dec 2018 00:00:00 +0000

Under this project, mainly two parts related to my Master work:

Taxonomic revision of Elaeagus L. (Elaeagnaceae) in China
Combined knowledges from field observations and comprehensive study on more than 7000 specimens from 20 herbaria, I have recognised of 36 species, one subspecies and five varieties in mainland China. 13 species names and three variety names are regarded as new synonyms. See more details in Sun et al. (2010)
Validation and lectotypification for all type specimens deposited in PE

A type is a really important object in taxonomy; it can be a particular specimen (in some cases a diagram, or a group of specimens) of an organism to which the scientific name of that organism is formally attached. Based on detailed study of 20,000 cited type specimens housed at China National Herbarium (PE) in litertures, we selected ca. 8,000 type specimens according to the updated International Code of Botanical Nomenclature. Our research was published as a book of Types Specimens in China National Herbarium (PE) (2015) with 15 volumes in total, and I’m the Coauthor of Vols. 6, 7, and 10. This book include type specimens from moss, ferns, and seed plants belong to 217 families, 1,174 genera, 6,627 species, 67 subspecies, 1,149 varities, and 126 forms; composed of 4,583 Holotypes, 2,372 Isotypes, 395 Lectotypes, 9 Isolectotypes, 3 Neotypes, 3 Isoepitypes, 34 Syntypes, 100 Isosyntypes, 293 Paratypes, 178 Isoparatypes. It was called as Masterpiece for research and study plants in China, and professional reference book for botanists, taxonomists, and systematists. All the type specimens were digitalized as high-resoluton images and its protologues referrences. Detailed information was recorded in databased. It perhaps be the most comprehensive collection of types specimens in the world. More information can be found from the publisher and China Daily.
This project was supported by Plant Specimen Digitisation and Chinese Virtual Herbarium Establishment.

15 Volums of Types Specimens in China National Herbarium (PE)

JSE: A revision of Elaeagnus L. (Elaeagnaceae) in mainland China

Sat, 01 May 2010 00:00:00 +0000

Primary Taxonomic Study of Elaeagnus ( Elaeagnaceae) in Mainland China

Mon, 01 Jun 2009 00:00:00 +0000