1001 - A tool for binary representations of unordered multistate characters (with examples from genomic data)

Mavrodiev E. V 1

1University of Florida, Florida Museum of Natural History, Gainesville, FL 32611 USA. [email protected]

s t n

i Abstract. In modern molecular systematics, matrices of unordered multistate characters, r

P such as DNA sequence alignments, are used for analysis with no further re-coding e r procedures nor any a priori determination of character polarity. Here we present 1001, a P simple freely available Python-based tool that helps re-code matrices of non-additive

characters as different types of binary matrices. Despite to the historical basis, our

analytical approach to DNA and protein data has never been properly investigated since

the beginning of the molecular age. The polarized matrices produced by 1001 can be used

as the proper inputs for Cladistic analysis, as well as used as inputs for future three-taxon

permutations. The 1001 binary representations of molecular data (not necessary

polarized) may also be used as inputs for different parametric software. This may help to

reduce the complicated sets of assumptions that normally precede either Bayesian or

Maximum Likelihood analyses.

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Introduction

In an un-polarized, binary matrix the states 0 and 1 do not represent a hypothesis

of character polarity. In an polarized binary matrix character-states 0 and 1 are considered

to be plesimorphic (“primitive”) and apomorphic (“derived”) respectively apriori to

analysis (see Kitching et al. 1998). Because in Cladistics groups must be define based s t n

i only on the synapomorphies (e. g., Donoghue and Maddison 1986, Williams and Ebach r

P 2008), it is critical to assume states’ polarity before analysis and group only on the states e r “1” of the polarized binary matrix (e. g., Platnick 1985, 2013, de Pinna, 1996, Williams P and Ebach 2008, Waegele, 2004, 2005). Therefore a fundamental problem in molecular

systematics today is that molecular matrices are not polarized (Waegele 2004, 2005) and

are therefore analytically uninformative form Cladistics standpoint (Williams and Ebach

2008).

Historically, polarized binary matrices were proposed as an ideal data format for

cladistics analysis following the argumentation schemes of Willi Hennig, who

determined each character’s polarity before the construction of a cladogram (e. g.,

Swofford and Begle 1993, Kitching et al. 1998, Waegele 2004, 2005, Williams and

Ebach 2008, Ebach et al., 2013, Wiley and Lieberman 2011). Hennigian logic may be

clear even from the pure methodological standpoint: without a character hypothesis in

place apriori to analysis, we are unable to test hypotheses aposteriori (Ebach, personal

note).

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Given this, we have developed 1001, a computer program that converts un-

polarized molecular data matrices into the different types of binary matrices, either un-

polarized or with established polarity.

Implementing 1001

1001 is implemented as Python-based script that translates conventional matrices s t n

i of unordered multisite characters into polarized and non-polarized binary matrices written r

P in Phylip or Comma Separated Values (CSV) file formats. 1001 can be used with any e r operating system that has a Python interpreter (e.g., Linux, Mac OS X, and Windows P (http://www.python.org/). Script been written by Dr. Matthew A . Gitzendanner

(University of Florida, Department of Biology and Florida Museum of Natural History,

Gainesville, FL 32611 USA).

1001 accepts DNA and amino acid sequence alignments, as well non-molecular

data, in “relaxed” PHYLIP format (e. g., Maddison and Maddson 2011). All gaps and

ambiguities of the conventional multistate matrices must be recoded as "?" ("missing

entities") before running of 1001. The DNA sequence data is the subject of our primary

interest and the default option of 1001 designed for these kind of data. However, the

script may handle different kinds of unordered multistate characters.

Figures 1 (A – C), 2 and 3 provide the summary and the explanation of the results

and methods. Both methods implemented by 1001 a priori polarize conventional data by

comparing with an assumed all-plesiomorphic outgroup, as it was proposed before for

morphological data. This way of re-coding led to the non-direct methods of polarity

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estimation, as defined by Nelson (1978)(reviewed in Nixon and Carpenter 1993, de Pinna

1994, Kitching et al. 1998, Bryant 2001). Also, as it was summarized by Nixon and

Carpenter (1993: 414), the earliest mention of “out-group comparison” belong to Platnick

and Gertch (1976)(reviewed in Nixon and Carpenter 1993, see also Platnick and Gertsch

1976: 2).

The first Method (Fig. 1B) is based on a standard bioinformatics technique

frequently cited as the “Vos representation” of DNA sequences (reviewed in Bernaola- s t n

i Galvan et al. 2002) or as “CODE-4 encoding” of DNA data (Demeler and Shou 1991: r

P 1594, see also absence/presence coding of Carine and Scotland 1999, Scotland 2000a, b e r and Pleijel 1995 (“Method D”), reviewed in Kitching et al. 1998), but, additionally, with P the re-coding of the resulted 1/0 matrix as the polarized binary matrix.

Eight output files resulted from each run of 1001, if the First Method selected:

- non-polarized binary matrix, with and without invariant characters removed

(both phy and csv files);

- polarized binary matrix, with and without invariant characters removed (both

phy and csv files);

The absence/presence coding may results the similar trees as obtained with the

regularly coded characters, or may bias the original multistate data (de Laet 2005: 94-96)

therefore an additional method of the binary representation of multistate data also

implemented in 1001. Additional ways of binary coding are also possible, at least for the

DNA characters (e. g., Bernaola-Galvan et al., 2002: 106, Table 1).

This second method (Fig. 1C), or as we prefer to call it the “Cladistic” Method,

directly represents the conventional multistate alignment as a set of maximum

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relationships (Williams and Ebach 2008) following the values of the pre-selected out-

group taxon (Fig. 1). This method is designed for the polarized binary outputs only

(available in both phy and csv formats).

Both proposed methods increase the number of parsimony-informative characters.

Both polarized and non-polarized binary 1001 outputs can be used with popular

phylogenetic software, with many different statistical packages as well as an input for

three-taxon permutations (Nelson and Platnick 1991) using TAXODIUM 1.2 (polarized s t n

i binary data only)(Mavrodiev and Madorsky 2012) for the future completion of the r

P Cladistics analysis. e r 1001 is available for free from the Web (https://github.com/magitz/1001) P

Breaking with the tradition of using unpolarized matrices in molecular systematics

Many popular phylogenetic applications are able to polarize characters before

analysis (e.g., command “AncState” of PAUP* (Swofford 2002) and “ancstates” of TNT

(Goloboff et al. 2008), see also the option “ancestors” included in some programs of

PHYLIP package (Felsenstein 1989). However our analytical approach to DNA and

protein data has never been properly investigated since the beginning of the molecular

age (Waegele 2004, 2005).

As clarified by Nixon and Carpenter (1993, 2012), by using unpolarized data,

modern phylogenetists are following Farris (1970, 1972, 1982)(see, however, Kluge

1976) and Meacham (1984)(reviewed Nixon and Carpenter, 1993, 2012, see also

Meacham, 1986 and Williams and Ebach 2008). For example, Meacham (1984, 1986)

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explicitly did not recommended to polarize characters before analysis, and was initially

strongly criticized for this position (Donoghue and Maddison 1986).

However, as was later clearly summarized by Swofford and Begle (1993: 3, 27) in

general agreement with Meacham (1984, 1986), it is better to infer the topology of the

tree and the character polarities simultaneously, rather than going through the two-stage

process of assigning polarities first and then estimating the tree (see also Maddison et al.,

1984, among others). s t n

i Maddison et al. (1984) and Swofford and Begle (1993) also noted that a priori r

P polarization of the characters is reasonable only when the polarity determination is e r unambiguous (i.e., there is no heterogeneity in the outgroup for characters that are P variable within the ingroup); when the outgroup is heterogeneous, and the most

parsimonious assignment of an ancestral condition for the ingroup depends upon how the

outgroup taxa are related to each other (Swofford and Begle 1993: 3, 27, see also

Maddison et al., 1984, Nixon and Carpenter, 1993, Maddison and Madison, 2011,

Kitching et al. 1998, Lyons-Weiler et al. 1998 among others).

In other words, if the number of taxa within the out-group is in some way reduced

to one (see Arnold 1989 among others including the TNT program (Goloboff et al. 2008)

that offer a single out-group taxon as a default option) (or also in the case of

homogeneous outgroup), for a character with two or more states, the state occurring in

the outgroup can be indeed assumed to be the plesiomorphic state (Platnick and Gertsch

1976: 2, see also Watrous and Wheeler, 1981, Bryant 2001, de Pinna 1994, Kitching et

al. 1998, Donoghue and Maddison 1986, and Nixon and Carpenter 1993 for the reviews).

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We believe that numerous analytical possibilities are still missed from this simple

cladistics perspective and therefore the 1001 may help to investigate the field better.

If the characters of conventional multistate matrix are polarized, then the data

are represented in the form of relations, either “maximum” or “minimum” (Williams and

Ebach 2008). One of the goals of 1001 is the explication of sets of “maximum

relationships” as separate entities (as polarized binary matrices) for future analyses. The

listed popular software (see above) is unable to perform such explications, even if in s t n

i principle these programs can polarize matrices before analyses. r

P Each relation is a not equal to the conventional character anymore, but represents e r the hypothesis of the relationships between taxa (e. g., Platnick et al. 1996, Williams and P Ebach 2008). Therefore the polarized binary matrix is semantically different from either

raw multistate alignment or from the non-polarized binary representation of this

alignment. One, for example, may note that the polarized binary matrix represents a kind

of structure, rather than the collection of raw characters.

Another may tell us that the notion that systematic data constitutes a normal

character by taxon matrix is not an intrinsically cladistic notion (Platnick 1993: 271, see

also Williams and Ebach 2006, 2008 and Ebach et al. 2013) and, therefore, another type

of data may require for the Cladistic analysis, especially if the last one is viewed as an

extension of comparative approach (e. g., Nelson and Platnick 1981, Williams and Ebach

2008, Rieppel et al., 2013, see also Nelson, 1970). The sets of maximum relationships

explicated by 1001 may be considered as putative candidates for the proper inputs for

Cladistic analysis.

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1001 and three-item analysis

It was argued multiple times, that the three-taxon matrix constitutes the actual

systematic data (e. g., Platnick 1993: 271, see also Nelson and Platnick 1991, Williams

and Siebert 2000 and Williams and Ebach 2008). However the three-taxon representation

of unordered multistate data may be an issue (Williams and Siebert 2000).

Scotland and others (Carine and Scotland 1999, Scotland 2000a, b) already s t n

i performed the three-taxon-permutations of non-additive binary data (eventually re-coded r

P multistate data). They also discussed their methodology in the context of Patterson’s idea e r of “pair homology” (Carine and Scotland 1999, Scotland 2000a, b). The polarized binary P outputs of 1001 may also be used as inputs for future three-taxon representations using

TAXODIUM 1. 2 (Mavrodiev and Madorsky 2012)(Fig. 2). As well as the Williams -

Siebert three-taxon representation of unordered multistate data (Williams and Siebert

2000, Mavrodiev and Madorsky 2012, Mavrodiev et al. 2014), this option may help to

prevent the artificial groupings under the conditions of 3TA, mentioned by Kluge and

Farris (1999) and Farris et al. (2001) in their comments of the results of Scotland and

others (Carine and Scotland 1999, Scotland 2000a, b).

1001 and parametric methodology

Below we argued that it is critical to break with the tradition of using unpolarized

matrices in molecular systematics. However even the non-polarized 1001-binary

representations of molecular data may essentially extend the horizons of conventional

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phylogenetic analyses. For example these representations may also be used as inputs for

parametric software and analyzed under the conditions of the simplest Mk model (Lewis,

2001) and it elementary binary derivates (Stamatakis 2014)(Fig. 3). This may help to

simplify the complicated sets of assumptions (Jefferys and Berger 1992, Berger and

Jefferys 1992) that normally precede either Bayesian or Maximum Likelihood

approaches increasing the “robustness” of the analyses (Berger and Jefferys 1992). More

investigation is necessary here, however. s t n

i r

P Conclusion e r P A fundamental problem in molecular systematics today is that molecular matrices are not

polarized. Historically, specifically polarized binary matrices were been proposed as an

ideal data format for Cladistic analysis following the argumentation schemes of Willi

Hennig, but despite of historical background, this analytical approach to the molecular

data, never been properly investigated. Given this, we have developed 1001, a simple

computer program that converts un-polarized molecular data matrices into the different

types of binary matrices, either un-polarized or with established polarity. Both methods

implemented by 1001 a priori polarize conventional data by comparing with an assumed

all-plesiomorphic outgroup, as it was proposed before for morphological data. The

polarized matrices explicated by 1001 may be considered as candidates for the proper

inputs for Cladistic analysis, as well as used as inputs for future three-taxon permutations.

The 1001 binary representations of molecular data (not necessary polarized) may also be

used as inputs for different parametric software. This may help to reduce the complicated

9

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sets of assumptions that normally precede either Bayesian or Maximum Likelihood

analyses.

s t n i r P e r P

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Acknowledgments

I thank Prof. Gareth Nelson for brief helpful discussion regarding the Cladistics

representation of the DNA characters (Method 2), as implemented in “1001”. I also thank

Dr. Matthew Gitzendanner for elegant Phyton-based implementation of “1001”. Finally, I

would like to acknowledge Drs. David Williams and Malte Ebach for their helpful

comments and linguistic remarks that help to sharp arguments. No agreement imply from s t n

i the behalf of any person acknowledged in this section. r

P e r P

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References

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Figure Legends

Fig. 1. A. Results of Maximum Parsimony Analyses (MP) of conventional plastid

genomic DNA matrix from Ma et al. 2014a, b. Final topologies rooted relatively

Dendrocalamus latiflorus Munro (Ma et al. 2014). Median Consensus Tree based on

Robinson-Foulds (RF) distance (with the best score found = 8837) of 184 shortest trees s t of length = 5019 (CI = 0.89, RI = 0.91). Number of taxa = 157. All constant characters n i r from the original alignment are excluded from the analysis. Number of variable P e characters = 4304, number of parsimony-informative characters = 2003. * nodes received r

P Maximum Parsimony Jackknife (JK) support >50% after 20 000 fast JK replicates; !

nodes recovered Maximum Parsimony Bootstrap support in the original analysis of Ma et

al. 2014 (200 full heuristic replicates). B. Results of Maximum Parsimony Analyses

(MP) of binary representation of conventional DNA matrix from A., re-coded following

proposed Method 1. Initial binary date were also polarized before analysis relatively D.

latiflorus, assumed as an outgroup based on the results of Ma et al. (2014a). Majority-

Rule Consensus of 191 shortest trees of length = 10014 (CI = 0.88, RI = 0.89). Number

of taxa = 157. Number of binary characters = 8783, number of parsimony-informative

characters = 4088. * nodes received Maximum Parsimony Jackknife (JK) support >50%

after 20 000 fast JK replicates. C. Results of Maximum Parsimony Analyses (MP) of

binary representation of conventional DNA matrix from A., re-coded following proposed

Method 2. Data polarized before analysis relatively latiflorus, assumed

as an out-group based on the results of Ma et al. 2014. Majority-Rule Consensus of 139

shortest trees of length = 4993 (CI = 0.89, RI = 0.91). Number of taxa = 157. Number of

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binary characters = 4993, number of parsimony-informative characters = 2027. * nodes

received Maximum Parsimony Jackknife (JK) support >50% after 20 000 fast JK

replicates.

All MP analyses were conducted using program PAUPrat (Nixon 1999; Sikes and

Lewis 2001; Swofford 2002) as implemented in CIPRES (Miller et al. 2010) following

200 ratchet replicates with no more than 1 tree of length greater than or equal to 1 saved

in each replicate, and the TBR branch swapping/MulTrees option in effect; -pct = 20%, s t n

i all characters weighted uniformly, gaps were treated as ‘‘missing”. Maximum Parsimony r

P jackknifing (Farris et al. 1996) conducted using program PAUP* (Swofford 2002). e r Robinson-Foulds consensus (reviewed in Kitching et al. 1998 and Bansal et al. 2010) P calculated using program RFS v. 2.0 (Bansal et al. 2010). Majority-Rule consensus

calculated in PAUP* (Swofford 2002).

All gaps and ambiguities of the conventional DNA matrix (A.) recoded as missing

data ("?") before binary permutations.

Roman numbers corresponds to the “major lineages” of , as specified by

Ma et al. 2014a.

Fig. 2. The results of two preliminary three-taxon analyses (3TAs) of Clades 1 and 2 of

the general topology, described on Fig. 1. In both cases, the DNA alignments derived

from described above (Fig. 1, all original data came from Ma et al. 2014a, b) simply by

proper sampling. These alignments been polarized following Method 2 and after that

established as a tree-taxon matices using TAXODIUM 1.2 (Mavrodiev, Madorsky,

2015). wilsonii (Rendle) C.S.Chao & C.D.Chu (Clade 1) and Bergbambos

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tessellata (Nees) Stapleton (Clade 2) assumed as an outgroup taxa before Method 2

applied to the DNA characters. A. The results of the first 3TA (Clade 1). Majority-Rule

Consensus of 193 shortest trees of length = 527046 (CI = 0.92, RI = 0.91). The number of

taxa in 487168 character-3TA matrix is 72. All 487168 3TSs are parsimony-informative

and weighted uniformly. B. The results of the second 3TA (Clade 2). Majority-Rule

Consensus of 201 shortest trees of length = 187857 (CI = 0.86, RI = 0.83). The number of

taxa in 161027 character-3TA matrix is 80. All 1610278 3TSs are parsimony-informative s t n

i and weighted uniformly. Roman Numbers corresponds to the “major lineages” of r

P bamboos, as specified by Ma et al. 2014a. See also the Legend of the Fig. 1 for the details e r of the MP analyses. P

Fig. 3. A. Most probable topology recovered from a Maximum Likelihood (ML) analysis

(RAxML)(Stamatakis 2014) of conventional Campanula s.l. & outgroups DNA plastid +

nuclear (PPR loci) combined matrix from Crowl et al. (2014). The names of the all taxa

are taken from the Supplemental data of Crowl et al. (2014). ML bootstrap (BS) values

for nodes receiving .50% supports are indicated above and below the branches (1000

rapid replicates). GTR + G model was assumed to be the best choice for the molecular

dataset. Final ML Optimisation Likelihood: -57876.127159. B. Most probable topology

recovered from Maximum Likelihood analysis (RAxML)(Stamatakis 2014) of

conventional Campanula s.l. & out-groups DNA plastid + nuclear (PPR loci) combined

matrix from Crowl et al. (2014), but established as a non-polarized binary matrix

following Method 1. Binary matrix analyzed under the assumptions of BINGAMMA

model (Stamatakis 2014, see also Lewis 2001) with the putative ascertainment bias

17

PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1153v1 | CC-BY 4.0 Open Access | rec: 2 Jun 2015, publ: 2 Jun 2015

(Lewis 2001) left uncorrected. ML bootstrap values for nodes receiving .50% supports

are indicated above and below the branches (1000 rapid ML BS replicates). Final ML

Optimisation Likelihood: -85930.633845.

s t n i r P e r P

18

PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1153v1 | CC-BY 4.0 Open Access | rec: 2 Jun 2015, publ: 2 Jun 2015 A. DNA characters B. Binary data: Method 1 C. Binary data: Method 2 (polarized binary example)

! nigra Clade 2 Clade 2 Phyllostachys edulis Clade 2 Phyllostachys edulis Phyllostachys edulis Phyllostachys nigra Phyllostachys propinqua * Phyllostachys propinqua * Phyllostachys propinqua * Phyllostachys nigra qingyuanensis Phyllostachys heteroclada A 1? Acidosasa notata Brachystachyum densiflorum A 011 seminuda wuyishanensis Phyllostachys heteroclada A 1? * Pleioblastus intermedia Pleioblastus solidus Pleioblastus amarus A 011 Sasa qingyuanensis T+ Pleioblastus juxianensis Sinobambusa seminuda 00 T+ 000 Pleioblastus juxianensis amabilis var. convexa oedogonatum Pseudosasa amabilis var. convexa A 1? Pseudosasa maculifera Pleioblastus solidus * ! A 011 * Pseudosasa maculifera Sinobambusa seminuda Pleioblastus wuyishanensis C ?1 Phyllostachys heteroclada * Acidosasa notata C 110 * Indocalamus victorialis Pleioblastus intermedia Sasa sinic a C ?1 Pleioblastus amarus Brachystachyum densiflorum Pleioblastus yixingensis C 110 Acidosasa notata T+ 00 Oligostachyum oedogonatum Pleioblastus sanmingensis T+ 000 Pleioblastus wuyishanensis Sasa qingyuanensis Pleioblastus juxianensis * Pleioblastus solidus Pleioblastus yixingensis Pleioblastus intermedia Pleioblastus yixingensis Pleioblastus sanmingensis ! Pseudosasa maculifera Sasa sinica Sasa sinica * Pseudosasa amabilis var. convexa Oligostachyum oedogonatum Pleioblastus amarus ! Indocalamus latifolius Pleioblastus sanmingensis Indocalamus latifolius Indocalamus victorialis Brachystachyum densiflorum Indocalamus victorialis Pseudosasa acutivagina Pseudosasa acutivagina Pseudosasa acutivagina ! sp. 2 patellaris Ampelocalamus patellaris

Gelidocalamuss rutilans ! * Ampelocalamus scandens Ampelocalamus scandens Indocalamt us tessellatus fargesii nitida * ! Indocalamus guangdongensis Arundinaria aristata * n Fargesia robusta

Indocalami us herktosii * Indocalamus quadratus Fargesia decurvata

Indocalamusr hirtivaginatus Indocalamus emeiensis Fargesia spathacea Fargesia nitida ! Pseudosasa hirta Fargesia qinlingensis

Fargesia robustP a ! Phyllostachys nidularia Indocalamus guangdongensis Fargesia decurvata yadongensis e * Indocalamus herktosii Fargesia spathacea Yushania basihirsuta r Gelidocalamus rutilans Fargesia qinlingensis ampullare * Gelidocalamus sp. 2 Indocalamus sp. * P * Drepanostachyum hookerianum Indocalamus hirtivaginatus Fargesia fungosa * Himilayacalamus falconeri Fargesia edulis Yushania brevipaniculata Drepanostachyum ampullare Yushania basihirsuta Yushania qiaojiaensis * Drepanostachyum hookerianum Phyllostachys nidularia Fargesia edulis * Himilayacalamus falconeri Yushania crassicollis Fargesia fungosa Yushania brevipaniculata Yushania baishanzuensis Yushania crassicollis Yushania qiaojiaensis Arundinaria spanostachya * Yushania baishanzuensis Fargesia fungosa Indocalamus bashanensis szechuanensis Arundinaria fargesii Yushania yadongensis Menstruocalamus sichuanensis Arundinaria aristata Ampelocalamus patellaris Fargesia macclureana Pseudosasa hirta Ampelocalamus scandens Arundinaria spanostachya Indocalamus emeiensis ! Drepanostachyum hookerianum ! Arundinaria abietina Indocalamus quadratus Drepanostachyum ampullare * fimbriatus Indocalamus longiauritus * Himilayacalamus falconeri ! Fargesia nitida Pseudosasa guangxiensis Yushania brevipaniculata * * Fargesia robusta Arundinaria qingchengshanensis Yushania qiaojiaensis * * Fargesia spathacea Indocalamus decorus Chimonobambusa szechuanensis Fargesia qinlingensis Indocalamus hirsutissimus Chimonocalamus fimbriatus Fargesia decurvata Fargesia yunnanensis Fargesia macclureana Indocalamus bashanensis Yushania levigata Arundinaria fargesii Indocalamus longiauritus Fargesia macclureana Arundinaria aristata Arundinaria qingchengshanensis Fargesia edulis Indocalamus emeiensis * * Pseudosasa guangxiensis Phyllostachys nidularia Pseudosasa hirta Indocalamus decorus Yushania maculata Indocalamus quadratus Indocalamus hirsutissimus Chimonocalamus pallens Arundinaria abietina Fargesia yunnanensis Chimonobambusa macrophylla Menstruocalamus sichuanensis * Yushania levigata Yushania basihirsuta Yushania maculata Chimonocalamus pallens Indocalamus bashanensis Arundinaria qingchengshanensis Chimonobambusa macrophylla Chimonocalamus fimbriatus * Indocalamus longiauritus Indocalamus wuxiensis Yushania yadongensis ! Pseudosasa guangxiensis Indocalamus guangdongensis Arundinaria abietina Indocalamus hirsutissimus * Indocalamus herktosii Arundinaria spanostachya V Indocalamus decorus * Gelidocalamus rutilans Menstruocalamus sichuanensis Chimonocalamus pallens Gelidocalamus sp. 2 Yushania crassicollis Chimonobambusa macrophylla * ! Indocalamus hirtivaginatus Yushania baishanzuensis Fargesia yunnanensis Indocalamus tessellatus Indocalamus wuxiensis Yushania levigata V Yushania maculata V Chimonobambusa szechuanensis Indocalamus wuxiensis Indocalamus sp. Indocalamus sp.

↑

Arundinaria faberi ↑ Arundinaria faberi Arundinaria faberi ↑ VII spathiflorus Thamnocalamus spathiflorus ! ! VII VII Thamnocalamus spathiflorus Chimonocalamus longiusculus Chimonocalamus longiusculus Chimonocalamus longiusculus !* Chimonocalamus dumosus * III ! * Chimonocalamus dumosus * Chimonocalamus dumosus * Chimonocalamus montanus III * Chimonocalamus montanus III Chimonocalamus montanus ↑ IX Ampelpcalamus actinotrichus Ampelpcalamus actinotrichus ↑ * Ampelpcalamus actinotrichus

Oldeania alpine ↑ IX ! ↑

II megalothyrsa Gaoligongshania↑ megalothyrsa IX

↑

Gaoligongshania megalothyrsa ↑ ↑ Oldeania alpine Oldeania alpine ↑ ↑ II ↑ II Indocalamus sinicus Indocalamus sinicus ↑ X Indocalamus sinicus Bergbambos tessellata X X I Bergbambos tessellata I Bergbambos tessellata I Clade 1 & Outgroups Clade 1 & Outgroups Clade 1 &Outgroups

+ - value of the assumed PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1153v1 | CC-BY 4.0 Open Access | rec: 2 Jun 2015, publ: 2 Jun 2015 Outgroup Fig. 1 A. DNA characters B. Binary data: Method 1 C. Binary data: Method 2 (polarized binary example)

Clade 1 & Outgroups Clade 1 & Outgroups Clade 1 & Outgroups

Indosasa sinica sinica ! Indosasa sp. Indosasa sinica ! Indosasa sp. Indosasa sp. Acidosasa purpurea Acidosasa purpurea Pleioblastus maculatus Acidosasa purpurea Pleioblastus maculatus Oligostachyum shiuyingianum Oligostachyum shiuyingianum Oligostachyum shiuyingianum Indosasa lipoensis Pleioblastus maculatus Indosasa lipoensis Indosasa gigantea ! Indosasa patens Acidosasa guangxiensis Acidosasa chienouensis * * Acidosasa guangxiensis * Acidosasa gigantea Indosasa patens Sinobambusa tootsik Oligostachyum sulcatum Acidosasa edulis Oligostachyum scabriflorum Pseudosasa cantorii Pseudosasa amabilis Sinobambusa intermedia Indosasa jinpingensis Indosasa lipoensis Indosasa gigantea Indosasa patens Pseudosasa orthotropa Acidosasa chienouensis Metasasa carinata * Acidosasa guangxiensis * Acidosasa gigantea Sinobambusa tootsik Acidosasa chinensis Acidosasa edulis Indosasa gigantea Indosasa hispida ! Pseudosasa viridula Indosasa spongiosa Acidosasa chienouensis Pseudosasa hindsii * Acidosasa edulis Oligostachyum gracilipes Pseudosasa cantorii Indosasa jinpingensis Acidosasa gigantea Indosasa hispida Indosasa triangulata Pseudosasa orthotropa

s Indosasa jinpingensis Arundinaria nanningensis Arundinaria nanningensis t Arundinaria nanningensis Clade 2 Indosasa hispida Clade 2 Clade 2 Pseudosasa viridula Oligostachyum gracilipes Sinobambusa intermedia Pseudosasa viriduln a

i Pseudosasa orthotropa Pseudosasa hindsii Pseudosasa hindsii r Oligostachyum sulcatum Indosasa triangulata Sinobambusa intermedia Indosasa spongiosa ↑ Indosasa crassiflora Oligostachyum lubricum ! P ↑ Metasasa carinata Pseudosasa cantorii ↑ Pseudosasa amabilis Indosasa triangulata Indosasa crassiflora Oligostachyume gracilipes * Pseudosasa amabilis Oligostachyum scabriflorum Oligostachyumr lubricum * ! Oligostachyum lubricum * Oligostachyum sulcatum Indosasa spongiosa Acidosasa chinensis

P Acidosasa chinensis * Oligostachyum scabriflorum Indosasa crassiflora Acidosasa nanunica * Metasasa carinata Acidosasa nanunica Indosasa glabrata ! Indosasa shibataeoides * Indosasa glabrata Indosasa glabrata ! Indosasa shibataeoides Indosasa shibataeoides Oligostachyum hupehense * Pseudosasa longiligula * * * Oligostachyum hupehense Pseudosasa longiligula Oligostachyum hupehense Pseudosasa longiligula Acidosasa nanunica * Pleioblastus sp * ! Pseudosasa japonica Pleioblastus argenteostriatus * Pseudosasa japonica var tsutsumiana Pseudosasa japonica var tsutsumiana ! * Pleioblastus pygmaeus * ! * Pleioblastus gramineus * Pleioblastus gramineus * Pseudosasa japonica var. tsutsumiana ! * Pleioblastus argenteostriatus Pleioblastus argenteostriatus Pseudosasa japonica * * Pleioblastus pygmaeus Pleioblastus pygmaeus * Pleioblastus gramineus Pleioblastus sp. * Pleioblastus sp. Sasa oblongula Sasa sp. 2 Sasa sp. 2 Sasa senanensis Sasa palmata VI VI Sasa sp. 1 Sasa sp. 1 Sasa sp. 1 ! Sasa senanensis VI Sasa senanensis Sasa oshidensis Sasa oblongula Sasa oblongula Sasa kurilensis * ! ramosa Sasaella ramosa ! Sasaella ramosa * * Sasa oshidensis Sasa oshidensis * Sasa kurilensis * Sasa kurilensis * Sasa sp. 2 * Sasa veitchii * Sasa veitchii Sasa palmata * Sasa tsuboiana Sasa tsuboiana ! Arundinaria appalachiana Arundinaria appalachiana Arundinaria appalachiana * Arundinaria tecta * Arundinaria tecta Arundinaria tecta * Arundinaria gigantea * ! * Arundinaria gigantea Arundinaria gigantea Sasa magnonoda ! Sasa longiligulata Sasa longiligulata * Sasa longiligulata ! * * Sasa magnonoda Sasa magnonoda Sasa guangxiensis * !* * Sasa guangxiensis * Sasa guangxiensis Pseudosasa gracilis Pseudosasa gracilis * Pseudosasa gracilis Indocalamus jinpingensis * Indocalamus jinpingensis Indocalamus jinpingensis ! rimosivaginus Ferrocalamus rimosivaginus Ferrocalamus rimosivaginus * Ferrocalamus strictus Ferrocalamus strictus Ferrocalamus strictus ! Indocalamus barbatus Indocalamus pseudosinicus Indocalamus pseudosinicus * Indocalamus pseudosinicus ! Indocalamus barbatus Indocalamus barbatus Indocalamus tongchunensis * * Indocalamus tongchunensis Indocalamus tongchunensis IV ! Gelidocalamus sp. 1 * * IV Gelidocalamus sp. 1 IV Gelidocalamus sp. 1 ! Shibatae hispidus Shibataea lanceifolia Shibataea lanceifolia ! * Shibatae chinensis * * Shibataea nanpingensis Shibataea nanpingensis * Shibataea lanceifolia * Shibatae hispidus Shibatae hispidus ! Shibataea nanpingensis * Shibatae chinensis Shibatae chinensis

* Gelidocalamus tessellatu↑ s

↑ * Gelidocalamus tessellatu↑ s Gelidocalamus tessellatus Indocalamus wilsonii ↑ * Indocalamus wilsonii ↑ VIII Indocalamus wilsonii ↑ Ampelocalamus calcareus VIII VIII IX Ampelocalamus calcareus Ampelocalamus calcareus ! Bambusa oldhamii IX Bambusa emeiensis Bambusa emeiensis IX * Bambusa emeiensis * Bambusa oldhamii Bambusa oldhamii Dendrocalamus latiflorus * Dendrocalamus latiflorus Dendrocalamus latiflorus (= assumed Out) (= assumed Out)

PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1153v1Fig. | CC-BY 1 (continious) 4.0 Open Access | rec: 2 Jun 2015, publ: 2 Jun 2015 3TA: Clade 1 3TA: Clade 2 A 1? 11?? A 1? 1?1? Indosasa sinica Indocalamus latifolius T+ ↑ 00 [to ↑ 3TSs] 0000 Indosasa sp. Indocalamus victorialis Acidosasa purpurea Pleioblastus juxianensis A 1? ?11? Oligostachyum shiuyingianum Sinobambusa seminuda Pleioblastus intermedia C ?1 ???1 Sinobambusa intermedia Sasa sinica C ?1 ???1 Oligostachyum sulcatum Pleioblastus sanmingensis Pseudosasa cantorii Pleioblastus yixingensis T+ 00 0000 Acidosasa chinensis Sasa qingyuanensis Indosasa crassiflora Pseudosasa maculifera Indosasa patens Pseudosasa amabilis var. convexa + - value of the assumed Outgroup Indosasa lipoensis Pleioblastus solidus (e. g., Bergbambos tessellata ) Sinobambusa tootsik Pleioblastus wuyishanensis Acidosasa guangxiensis Acidosasa notata Arundinaria nanningensis Oligostachyum oedogonatum Phyllostachys heteroclada Pseudosasa viridula Pleioblastus amarus Pleioblastus maculatus Brachystachyum densiflorum Oligostachyum scabriflorum Phyllostachys edulis Indosasa spongiosa Phyllostachys nigra Metasasa carinata Phyllostachys propinqua Acidosasa edulis Pseudosasa acutivagina s Gelidocalamus sp. 2

t Acidosasa gigantea Indosasa gigantea Gelidocalamus rutilans

n Acidosasa chienouensis Indocalamus hirtivaginatus i Indosasa hispida Indocalamus guangdongensis r Indocalamus herktosii Indosasa jinpingensis Indocalamus tessellatus

P Oligostachyum lubricum Indocalamus decorus Pseudosasa hindsii Indocalamus hirsutissimus e Oligostachyum gracilipes Menstruocalamus sichuanensis r Pseudosasa amabilis Fargesia fungosa Pseudosasa orthotropa Chimonobambusa szechuanensis P Indosasa triangulata Arundinaria aristata Acidosasa nanunica Indocalamus emeiensis Indosasa glabrata Pseudosasa hirta Pseudosasa longiligula Arundinaria abietina Fargesia decurvata Oligostachyum hupehense Fargesia robusta Indosasa shibataeoides Fargesia qinlingensis Pseudosasa japonica var. tsutsumiana Chimonocalamus fimbriatus Pseudosasa japonica Chimonobambusa macrophylla Pleioblastus gramineus Yushania maculata Pleioblastus pygmaeus Fargesia macclureana Pleioblastus argenteostriatus Indocalamus sp. Pleioblastus sp. Yushania yadongensis Sasa veitchii Arundinaria spanostachya Yushania crassicollis Sasa kurilensis Yushania baishanzuensis Sasaella ramosa Fargesia edulis Sasa oblongula Phyllostachys nidularia Sasa sp. 2 Yushania brevipaniculata Sasa palmata Yushania qiaojiaensis VI Sasa tsuboiana Ampelocalamus patellaris Sasa sp. 1 Drepanostachyum hookerianum Sasa senanensis Drepanostachyum ampullare Sasa oshidensis Himilayacalamus falconeri Arundinaria appalachiana Arundinaria fargesii Fargesia spathacea Arundinaria tecta Fargesia nitida Arundinaria gigantea Arundinaria faberi Shibatae hispidus Fargesia yunnanensis Shibatae chinensis Yushania levigata Shibataea lanceifolia Ampelocalamus scandens Shibataea nanpingensis Chimonocalamus pallens Gelidocalamus tessellatus Indocalamus quadratus Indocalamus barbatus Yushania basihirsuta Indocalamus pseudosinicus Indocalamus bashanensis Gelidocalamus sp. 1 Indocalamus wuxiensis Pseudosasa guangxiensis Indocalamus tongchunensis V Arundinaria qingchengshanensis IV Sasa guangxiensis Indocalamus longiauritus Sasa magnonoda Indocalamus sinicus Sasa longiligulata Chimonocalamus longiusculus Pseudosasa gracilis Chimonocalamus dumosus Ferrocalamus rimosivaginus III Chimonocalamus montanus

Ferrocalamus strictus Ampelpcalamus ↑ actinotrichus

Oldeania alpine II ↑

Indocalamus jinpingen↑ sis Indocalamus wilsonii VIII Gaoligongshania megalothyrsa ↑ IX (= assumed Outgroup) Thamnocalamus spathifloru↑ s VII Bergbambos tessellata I (= assumed Outgroup) A. B.

Fig. 2 PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1153v1 | CC-BY 4.0 Open Access | rec: 2 Jun 2015, publ: 2 Jun 2015 A. DNA characters/RAxML 6 7 Campanula brixiensis 3 Campanula brixiensis 3 6 6 Campanula brixiensis 4 B. Binary data: Method 1/RAxML 100 6 9 9 5 Campanula brixiensis 4 Campanula brixiensis (non-polarized 9 1 Campanula brixiensis Campanula brixiensis 2 Campanula brixiensis 2 Campanula marchesettii binary example) 5 2 Campanula marchesettii Campanula marchesettii 2 Campanula marchesettii 2 8 4 Campanula rotundifolia Campanula rotundifolia Campanula bertolae 2 9 3 9 7 Campanula bertolae 2 Campanula bertolae 3 9 8 Campanula bertolae 3 Campanula bertolae Campanula bertolae Campanula sabatia Campanula sabatia Campanula carnica Campanula carnica 9 9 Campanula carnica cfr. 100 Campanula forsythii Campanula forsythii Campanula macrorhiza Campanula macrorhiza 9 9 6 2 A 001 100 Campanula carnica cfr. Campanula appenina 7 2 Campanula appenina 5 4 Campanula stenocodon Campanula stenocodon Campanula rhomboidalis 7 1 A 001 7 4 7 5 Campanula rhomboidalis Campanula witasekiana Campanula scheuchzeri Campanula scheuchzeri Campanula witasekiana 100 T 010 100 9 6 Campanula herminii Campanula arvatica 9 8 Campanula arvatica Campanula herminii Campanula caespitosa 100 A 001 100 Campanula caespitosa 9 9 Campanula cochlearifolia 5 2 100 6 7 Campanula cochlearifolia Campanula fragilis C 100 Campanula fragilis Campanula excisa 7 1 100 9 8 Campanula excisa Campanula cenisia 100 Campanula cenisia Campanula elatinoides C 100 100 100 Campanula elatinoides 100 Campanula divaricata 100 Campanula parryi Campanula parryi T 010 100 9 9 Campanula divaricata Campanula hawkinsiana 100 Campanula hawkinsiana 9 9 Campanula versicolor 100 100 Campanula versicolor Campanula pyramidalis 100 Campanula pyramidalis 100 Campanula carpatica 100 Campanula carpatica 100 Campanula spatulata cfr. 100 9 7 Campanula spatulata cfr. Campanula spatulata 9 8 Campanula spatulata 9 6 100 Campanula rapunculus 100 100 100 Campanula rapunculus Campanula patula 100 s Campanula patula 9 5 Campanula lusitanica

t Campanula lusitanica Campanula elatines 9 8 100 Campanula portenschlagiana Campanula portenschlagiana 100 100 100 Campanula elatines n Campanula aizoides

i Campanula aizoides Hanabusaya asiatica Hanabusaya asiatica r Legousia speculum veneris 100 Legousia hybrida 8 1 Legousia hybrida 100 9 7 9 3 Legousia speculum veneris

P Physoplexis comosa 100 Physoplexis comosa Legousia pentagonia 100 Legousia pentagonia 7 4 Legousia falcata e 100 8 4 Legousia falcata 9 1 Campanula reverchonii r Campanula reverchonii 100 Triodanis coloradoensis 9 8 100 Triodanis coloradoensis Asyneuma virgatum 8 7 8 9 Asyneuma virgatum P Petromarula pinnata Petromarula pinnata 9 1 Campanula cretica 9 6 Campanula cretica 100 Githopsis pulchella 9 9 Githopsis diffusa 100 Githopsis pulchella 9 9 7 1 100 100 Githopsis diffusa Heterocodon rariflorum 7 9 100 Campanula exigua 100 Heterocodon rariflorum 100 Campanula exigua Campanula scouleri 100 Campanula robinsiae Campanula scouleri Campanula robinsiae 8 8 Campanula persicifolia 8 4 6 4 Campanula grossheimii Campanula persicifolia 100 Campanula rapunculoides 6 9 Campanula grossheimii 8 2 100 Campanula rapunculoides Campanula bononiensis 8 8 9 0 Campanula alliariifolia Campanula bononiensis 9 8 Campanula alliariifolia 6 8 Symphyandra pendula 9 7 Campanula aucheri 100 7 7 Symphyandra pendula Campanula bellidifolia Campanula aucheri 7 0 Campanula bellidifolia Campanula macrostachya 7 7 Campanula sibirica 5 7 Campanula macrostachya Campanula sibirica Campanula trachelium 6 3 Campanula mirabilis Campanula trachelium Campanula saxatilis Campanula mirabilis Campanula incurva 100 Symphyandra armena 5 2 Michauxia tchihatchewii 100 Campanula saxatilis Symphyandra armena Campanula hierapetrae 6 7 100 Campanula thyrsoides Michauxia tchihatchewii 8 7 Campanula spicata Campanula hierapetrae 100 Campanula spicata Campanula petraea 9 1 Campanula glomerata Campanula thyrsoides Campanula cervicaria Campanula petraea Symphyandra hofmanni Symphyandra hofmanni Campanula alpestris Campanula glomerata Campanula alpestris Campanula foliosa 6 1 Campanula lanata Campanula cervicaria 5 7 Campanula foliosa 5 4 Edraianthus graminifolius Campanula lanata 9 5 Campanula carpatha Campanula laciniata 100 Edraianthus graminifolius 8 6 Campanula pelviformis 6 3100 Campanula carpatha Campanula laciniata 9 9 Campanula tubulosa 7 4 100 9 8 Campanula pelviformis 9 5 Campanula sarmatica 6 5 Campanula medium 100 100 Campanula tubulosa 100 Campanula barbata 9 9 Campanula sarmatica Campanula latifolia Campanula medium Campanula incurva Campanula barbata Campanula latifolia 100 Campanula jacquinii 100 9 5 Campanula mollis Campanula jacquinii 9 5 Campanula edulis 9 5 Campanula mollis 100 9 5 Campanula edulis Feeria angustifolia 100 Azorina vidalii Feeria angustifolia 100 Azorina vidalii 8 6 9 5 100 100 Campanula erinus 100 100 8 8 100 Campanula drabifolia Campanula drabifolia 100 Campanula creutzburgii Campanula erinus Trachelium caeruleum Campanula creutzburgii 100 Campanula peregrina Trachelium caeruleum 9 1 Musschia aurea 100 Campanula peregrina 100 9 6 Musschia aurea Gadellia lactiflora 100 Campanula lactiflora Gadellia lactiflora Campanula lactiflora 100 9 9 Jasione crispa 6 8 9 4 Jasione heldreichii 100 9 9 Jasione crispa 100 9 8 Jasione heldreichii Jasione laevis 100 Jasione montana Jasione laevis Wahlenbergia hederacea Jasione montana 100 Wahlenbergia gloriosa Wahlenbergia hederacea 9 7 Wahlenbergia angustifolia 100 Wahlenbergia gloriosa 100 Merciera tenuifolia 100 Wahlenbergia angustifolia 100 Merciera tenuifolia 100 100 Wahlenbergia linifolia Wahlenbergia berteroi 100 100 Wahlenbergia berteroi Heterochaenia ensifolia Wahlenbergia linifolia Heterochaenia ensifolia 100 Platycodon grandiflorus CanarinaPeerJ PrePrints canariensi |s https://dx.doi.org/10.7287/peerj.preprints.1153v1 | CC-BY 4.0 Open Access100 | rec: 2 Jun 2015,Canarina publ: canariensi2 Jun 2015s Cyphia elata Platycodon grandiflorus Fig. 3 Cyphia elata