4 Corresponding Authors: 5 Iris Fischer (irisfischer402 ... Iris Fischer ([email protected]) and Nathalie Chantret ([email protected]) 6 INRA SupAgro, UMR AGAP, 2 Place

1

Running title: 1

Evolutionary dynamics of the LRR-RLK gene family 2

3

Corresponding Authors: 4

Iris Fischer ([email protected]) and Nathalie Chantret ([email protected]) 5

INRA SupAgro, UMR AGAP, 2 Place Pierre Viala, Bât. 21, 34060 Montpellier, France 6

Telephone: +33 (0)4 99 61 60 83 7

8

Research Area: Genes, Development and Evolution 9

Plant Physiology Preview. Published on January 15, 2016, as DOI:10.1104/pp.15.01470

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2

Evolutionary dynamics of the Leucine-Rich Repeats Receptor-Like Kinase 10

(LRR-RLK) subfamily in angiosperms. 11

12

13

Iris Fischer1,*, Anne Diévart2, Gaetan Droc2, Jean-François Dufayard2 and Nathalie Chantret1,* 14 15 1 INRA, UMR AGAP, F-34060 Montpellier, France 16 2 CIRAD, UMR AGAP, F-34398 Montpellier, France 17 *Corresponding Authors 18

19

Summary: Phylogenetic analysis of leucine-rich repeat containing receptor-like kinases 20

demonstrates the dynamic nature of gene duplication, loss and selection in this family. 21



3

I.F., A.D., and N.C. designed the study; G.D. performed the LRR-RLK extraction; J-F.D. 22

performed the phylogenetic clustering; I.F., A.D., and N.C. performed the data analysis and 23

statistics; I.F. drafted the manuscript with the help of A.D. and N.C. 24

25

Financial sources: IF was funded by the German Research Foundation (DFG): FI 1984/1-1 26

and the ARCAD project (Agropolis Resource Center for Crop Conservation, Adaptation and 27

Diversity) of the Agropolis Foundation. This work was partially funded by grant #ANR-08-28

GENM-021 from Agence Nationale de la recherche (ANR, France). 29

30

Corresponding Authors: 31

Iris Fischer ([email protected]) and Nathalie Chantret ([email protected]) 32



4

ABSTRACT 33

Gene duplications are an important factor in plant evolution and lineage specific expanded 34

(LSE) genes are of particular interest. Receptor-like kinases (RLK) expanded massively in 35

land plants and Leucine-Rich Repeat (LRR)-RLKs constitute the largest RLK family. Based 36

on the phylogeny of 7,554 LRR-RLK genes from 31 fully sequenced flowering plant 37

genomes, the complex evolutionary dynamics of this family was characterized in depth. We 38

studied the involvement of selection during the expansion of this family among angiosperms. 39

LRR-RLK subgroups harbor extremely contrasted rates of duplication, retention or loss and 40

LSE copies are predominantly found in subgroups involved in environmental interactions. 41

Expansion rates also differ significantly depending on the time when rounds of expansion or 42

loss occurred on the angiosperm phylogenetic tree. Finally, using a dN/dS-based test in a 43

phylogenetic framework, we searched for selection footprints on LSE and single-copy LRR-44

RLK genes. Selective constraint appeared to be globally relaxed at LSE genes and codons 45

under positive selection were detected in 50% of them. Moreover, the LRR domains – and 46

specifically four amino acids in them – were found to be the main targets of positive selection. 47

Here, we provide an extensive overview of the expansion and evolution of this very large 48

gene family. 49



5

INTRODUCTION 50

Receptor-like kinases (RLK) comprise one of the largest gene families in plants and expanded 51

massively in land plants (Embryophyta) (Lehti-Shiu et al., 2009; Lehti-Shiu et al., 2012). For 52

plant RLK gene families, the functions of most members are often not known (especially in 53

recently expanded families) but some described functions include innate immunity (Albert et 54

al., 2010), pathogen response (Dodds and Rathjen, 2010), abiotic stress (Yang et al., 2010), 55

development (De Smet et al., 2009), and sometimes multiple functions (Lehti-Shiu et al., 56

2012). The RLKs usually consist of three domains: an amino-terminal extracellular domain 57

(ECD), a transmembrane (TM) domain, and a carboxy-terminal kinase domain (KD). In 58

plants, the KD usually has a serine/threonine specificity (Shiu and Bleecker, 2001) but 59

tyrosine specific RLKs were also described (e.g. BRASSINOSTEROID INSENSITIVE1 (Oh 60

et al., 2009)). Interestingly, it was estimated that ~20% of RLKs contain a catalytically 61

inactive KD (e.g. STRUBBELIG, CORYNE (Chevalier et al., 2005; Castells and 62

Casacuberta, 2007; Gish and Clark, 2011)). In Arabidopsis, 44 RLK subgroups (SG) were 63

defined by inferring the phylogenetic relationships between the KDs (Shiu and Bleecker, 64

2001). Interestingly, different SGs show different duplication/retention rates (Lehti-Shiu et 65

al., 2009). Specifically, RLKs involved in stress response show a high number of tandemly 66

duplicated genes whereas those involved in development do not (Shiu et al., 2004) which 67

suggests that some RLK genes are important for responses of land plants to a changing 68

environment (Lehti-Shiu et al., 2012). There seem to be relatively few RLK pseudogenes 69

compared to other large gene families and copy retention was argued to be driven by both, 70

drift and selection (Zou et al., 2009; Lehti-Shiu et al., 2012). As most SGs are relatively old 71

and RLK subfamilies expanded independently in several plant lineages, duplicate retention 72

cannot be explained by drift alone and natural selection is expected to be an important driving 73

factor in RLK gene family retention (Lehti-Shiu et al., 2009). 74

Leucine-Rich Repeat (LRR)-RLKs, which contain up to 30 LRRs in their extracellular 75

domain, constitute the largest RLK family (Shiu and Bleecker, 2001). Based on the kinase 76

domain, 15 LRR-RLK SGs have been established in Arabidopsis (Shiu et al., 2004; Lehti-77

Shiu et al., 2009). So far, two major functions have been attributed to them: defense against 78

pathogens and development (Tang et al., 2010b). LRR-RLKs involved in defense are 79

predominantly found in lineage specific expanded (LSE) gene clusters whereas LRR-RLKs 80

involved in development are mostly found in non-expanded groups (Tang et al., 2010b). It 81

was also discovered that the LRR domains are significantly less conserved than the remaining 82

domains of the LRR-RLK genes (Tang et al., 2010b). In addition, a study on four plant 83



6

genomes (A. thaliana, grape, poplar, rice) showed that LRR-RLK genes from LSE gene 84

clusters show significantly more indication of positive selection or relaxed constraint than 85

LRR-RLKs from non-expanded groups (Tang et al., 2010b). 86

The genomes of flowering plants (angiosperms) have been shown to be highly dynamic 87

compared to most other groups of land plants (Leitch and Leitch, 2012). This dynamic is 88

mostly caused by the frequent multiplication of genetic material, followed by a complex 89

pattern of differential losses (i.e. the fragmentation process) and chromosomal rearrangements 90

(Langham et al., 2004; Leitch and Leitch, 2012). Most angiosperm genomes sequenced so far 91

show evidence for at least one whole genome multiplication event during their evolution (see 92

e.g. Jaillon et al. (2007); D'Hont et al. (2012); The Tomato Genome Consortium (2012)). At a 93

smaller scale, tandem and segmental duplications are also very common in angiosperms (The 94

Arabidopsis Genome Initiative, 2000; International Rice Genome Sequencing Project, 2005; 95

Rizzon et al., 2006). Although the most common fate of duplicated genes is to be 96

progressively lost, in some cases they can be retained in the genome and adaptive as well as 97

non-adaptive scenarios have been discussed to play a role in this preservation process (for 98

review see Moore and Purugganan (2005); Hahn (2009); Innan (2009); Innan and Kondrashov 99

(2010)). Whole genome sequences also revealed that the same gene may undergo several 100

rounds of duplication and retention. These lineage specific expanded genes were shown to 101

evolve under positive selection more frequently than single-copy genes in angiosperms 102

(Fischer et al., 2014). The study by Fischer et al. analyzed general trends over whole 103

genomes. Here, we ask if, and to what extent, this trend is observable at LRR-RLK genes. As 104

this gene family is very dynamic and large – and in accordance with the results of Tang et al. 105

(2010b) – we expect the effect of positive selection to be even more pronounced than in the 106

whole genome average. 107

We analyzed 33 Embryophyta genomes to investigate the evolutionary history of the 108

LRR-RLK gene family in a phylogenetic framework. Twenty LRR-RLK subgroups were 109

identified and from this dataset we deciphered the evolutionary dynamics of this family within 110

angiosperms. The expansion/reduction rates were contrasted between SGs and species as well 111

as in ancestral branches of the angiosperm phylogeny. We then focused on genes which 112

number increased dramatically in a subgroup- and/or species-specific manner (i.e. LSE 113

genes). Those genes are likely to be involved in species-specific cellular processes or adaptive 114

interactions and were used as a template to infer the potential occurrence of positive selection. 115

This led to the identification of sites on which positive selection likely acted. We discuss our 116

results in the light of angiosperm genome evolution and current knowledge of LRR-RLK 117



7

functions. Positive selection footprints identified in LSE genes highlight the importance of 118

combining evolutionary analysis and functional knowledge to guide further investigations. 119

120

121

122



8

RESULTS 123

We extracted genes containing both LRRs and a KD from 33 published Embryophyte 124

genomes. Here, we mostly describe the findings for the 31 angiosperm (eight monocot and 23 125

dicot) genomes we analyzed. The 7,554 LRR-RLK genes were classified in 20 subgroups 126

(SGs). This classification was inferred using distance related methods because the high 127

number of sequences to be analyzed would imply excessive computation time for methods 128

relying on maximum likelihood. Since we decided to study the evolutionary dynamic of LRR-129

RLK gene family using the SG classification as a starting point, we first wanted to verify that 130

each SG was monophyletic. Ten subsets of about 750 sequences were created by picking one 131

sequence out of ten to infer a PHYML tree (data not shown). Analysis of the trees shows that 132

most SGs (14) are monophyletic with strong branch support. On the other hand, for six SGs 133

(SG_I, SG_III, SG_VI, SG_Xb, SG_XI and SG_XV), the topology differs slightly between 134

trees: in at least five trees out of ten, either the SG appears to be paraphyletic or few 135

sequences are placed outside the main monophyletic clade with low branch support. As we 136

could not confirm that these SG are monophyletic, they were tagged with a "*" throughout the 137

manuscript. 138

Next, we determined the number of ancestral genes present in the last common ancestor 139

of angiosperms (LCAA) using a tree reconciliation approach (see Materials and Methods). In 140

short, tree reconciliation compares each SG-specific LRR-RLK gene tree to the species tree to 141

infer gene duplications and losses. Note that since only LRR-RLKs with at least one complete 142

LRR were considered, some of the inferred gene losses might correspond to RLKs without, or 143

with degenerated LRRs. Using this method, we predicted the number of LRR-RLK genes in 144

the LCAA to be 150. All SGs were present in the LCAA but the number of genes between 145

SGs was highly variable (Table I). SG_III* and SG_XI* show the highest number of ancestral 146

genes, with 32 and 29 genes, respectively. The lowest numbers of ancestral genes are 147

recorded for SG_VIIb, SG_Xa, SG_XIIIa, and SG_XIIIb which only possessed two genes and 148

SG_XIV which only contained one. These results show that already in the LCAA that lived 149

~150 million years ago (Supplemental Table SI) some SGs were more prone to retain copies 150

than others. We wanted to determine if this ancestral pattern was preserved during the course 151

of angiosperm evolution and if different SGs expanded or contracted compared to the LCAA. 152

153

Expansion rates of LRR-RLK genes differ between subgroups and species 154

To gain a more comprehensive understanding of LRR-RLK evolution, we first looked at SG-155

specific expansion rates in two complementary ways. First, we calculated the global SG 156



9

expansion rate (= ratio of contemporary LRR-RLK genes per species in one SG divided by 157

the ancestral number) for each SG (Fig. 1). Second, we inferred the branch-specific expansion 158

rate of each SG on the phylogenetic tree of the 31 angiosperm species. We did this by 159

automatically computing the ratio of descendant LRR-RLKs divided by the ancestral number 160

of LRR-RLKs at every node (see Materials and Methods) (Fig. 2). Looking at the global SG 161

expansion, we found that SG_Xa, SG_XIIa, SG_XIIb, and SG_XIV expanded more than 2-162

fold on average, and SG_I* and SG_IX around 2-fold (Fig. 1, Supplemental Table SII). 163

Interestingly, SG_XIIa already had a moderate-high ancestral gene number (nine) and 164

therefore seems to be generally prone to high retention rates. Indeed, SG_XIIa was subject to 165



10

repeated rounds of major expansion events (i.e. expansion > 2-fold) during its evolutionary 166

history, e.g. in Poaceae, the Solanum ancestor, Malvaceae, and the Arabidopsis ancestor; but 167

also species-specific expansions, e.g. in THECC, GOSRA, ARALY, SCHPA, MALDO, 168

LOTJA, POPTR, and JATCU (Fig. 2, see Table II for five-digit species code). On the other 169

hand, SG_I* and SG_XIIb had a medium number of copies in the ancestral genome (seven 170

and four, respectively) but the pattern of expansion is quite different when analyzed in detail 171

(Fig. 2). For SG_I*, the expansion rate is mostly due to ancestral expansion events rather than 172

species-specific ones. For example, the high number of copies in ARATH and EUTSA (Fig. 173

1) is not due to expansions specific to these species but rather an expansion in Brassicaceae. 174



11

Subsequently, copies were lost in the other species of this family analyzed here (ARALY, 175

SCHPA, BRARA) but retained in ARATH and EUTSA (Fig. 2). Species-specific expansions 176

can also be observed in SG_I*, mostly in PRUPE and POPTR. For SG_XIIb, on the other 177

hand, the high expansion rate is mostly due to recent species-specific expansions in PHODC, 178

MUSAC, VITVI, GOSRA, MALDO, POPTR, and JATCU. But one major ancestral 179

expansion can be observed in Rosids. 180

SG_IX, SG_Xa, and SG_XIV had only few copies in the LCAA (three, two, and one, 181

respectively) and all show a relatively high global expansion rate (Fig. 1). For these 182

subgroups also, a contrasted branch-specific expansion patterns can be observed (Fig. 2). 183

SG_Xa went through relatively few major expansions: one can be detected in the dicots 184

ancestor and a species-specific one in POPTR. Likewise, SG_IX shows only one ancestral 185

expansion in Malvaceae but more species-specific expansions in PHODC, MUSAC, 186

MALDO, and GLYMA. Finally, SG_XIV went through several rounds of ancestral 187

(monocots, dicots, Malvaceae, and Brassicaceae) as well as species-specific expansion 188

(PHODC, MALDO, and POPTR). The other SGs show a moderate expansion rate (1.3-1.75) 189

or no expansion at all (Fig. 1, Supplemental Table SII). SG_XV* is the only SG for which the 190

number of copies was decreasing on average compared to the LCAA genome (0.77). It is 191

important to note that the LCAA ancestral gene number could have been slightly over-192

estimated for those SGs without a confirmed monophyletic origin (denoted by “*”), resulting 193

in an under-estimation of global expansion rate. However, we re-calculated the global 194

expansion rates for each of those SGs using the largest subset of sequence that always include 195

a stable monophyletic clade. The obtained global expansion rate differed only slightly from 196

the ones presented here (data not shown) and the conclusions drawn remain unchanged. 197

Because some species underwent whole genome duplication (WGD) or whole genome 198

triplication (WGT) relatively recently compared to others (Table III), we determined species-199

specific patterns of LRR-RLK expansions and looked if those patterns are consistent with the 200

recent history of the species. Therefore, we computed the global species expansion rate (= 201

ratio of LRR-RLK genes per SG in one species divided by the ancestral number) for each of 202

the 31 angiosperm species. As expected, the global expansion rate differs significantly 203

between species (Fig. 3, Supplemental Table SII). Compared to the LCAA (150 genes), the 204

number of LRR-RLK genes did not decrease for most species except for LOTJA (114) and 205

CARPA (127). This indicates that, on average, LRR-RLK genes are more prone to retention 206

than loss. Some species, however, did not significantly expand their average number of LRR-207

RLK genes compared to the common ancestor: PHODC (158), CUCME (149), CUCSA 208



12

(180), SCHPA (194), BRARA (185), MEDTR (183), and RICCO (182). LRR-RLK genes 209

expanded more than 2-fold in GLYMA (477), MALDO (441), POPTR (400), and GOSRA 210

(372), and around 2-fold in MUSAC (280), MAIZE (241), SETIT (301), ORYSJ (317), 211

ORYSI (301), SOLTU (254), PRUPE (260), MANES (238), and EUTSA (240). The 212

remaining species show a moderate expansion rate (1.4-1.75): CACJA (222), THECC (238), 213

JATCU (208), ARATH (222), SOLLC (232), SORBI (225), BRADI (225), VITVI (193), and 214



13

ARALY (195). As expected, the four species with the highest global expansion rate 215

(GLYMA, MALDO, POPTR, GOSRA) are recent polyploids in which most SGs have 216

expanded (Fig. 2). However, some SGs expanded more than 2-fold, indicating that small scale 217

duplication events have occurred in addition to polyploidy. In POPTR, for instance, the global 218

expansion rates of SG_Xa and SG_XIIb are more than 8-fold (Fig. 3) and a strong branch-219

specific expansion rate is detected on the terminal POPTR branch (3.25 for SG_Xa and 5.4 220



14

for SG_XIIb) (Fig. 2). Surprisingly, SG_VIIa and SG_VIIb show a high branch-specific 221

expansion rate in POPTR (4.0 and 3.0, respectively), which is not reflected in the global 222

expansion rate in this species (Fig. 3). This is due to the fact that SG_VIIa and SG_VIIb went 223

through strong reduction in Malpighiales (0.33) and Fabids (0.5), respectively. Thus, the 224

cumulative effect of successive reductions and expansions is not evident in the global 225

expansion rate. These contrasted evolutionary dynamics can also be observed in MALDO. A 226



15

global expansion of SG_IX was not detected because of the strong reduction in 227

Amygdaloideae. To summarize, this data can be integrated into the species phylogeny to draw 228

an image of the complex evolutionary dynamics of the LRR-RLK gene family through time 229

(Fig. 4). 230

231

Different patterns of lineage specific expansion in LRR-RLK subgroups 232

Given the differences of LRR-RLK expansion rates between species, we wanted to identify 233

cases of LSE, i.e. cases where a high duplication/retention rate is specific to one species. 234

Using a tree reconciliation approach (see Materials and Methods), we built a dataset 235

consisting of ultraparalog clusters (UP – only related by duplication) which represents the 236

LSE events and a superortholog reference gene set (SO – only related by speciation). We only 237

considered clusters containing five or more sequences. After cleaning, our final dataset 238

comprised 75 UP and 189 SO clusters containing 796 and 1,970 sequences, respectively 239

(Table IV). The median number of sequences in the UP clusters is not significantly different 240

from the median number in SO clusters (8 in both cases) (Supplemental Fig. S1). For UP 241

clusters, however, the alignments are significantly longer (Mann-Whitney test: p<0.001) with 242

a median of 3,237 base pairs (bp) compared to 2,841 for SO clusters. One possible 243

explanation for this could be that UP clusters are more dynamic and might contain more 244

LRRs. PRANK, the alignment algorithm we used, introduces gaps instead of aligning 245

ambiguous sites and therefore produces longer alignments when sequences are divergent. 246

However, this phenomenon does not influence the outcome of further test for positive 247

selection using codeml (Yang, 2007). 248

We then wanted to determine which SGs are represented in the SO and UP dataset. 249

Unsurprisingly, all SGs were present in SO clusters (Fig. 5). This could be expected as all 250

SGs were already present in the LCAA and remained stable or expanded (except SG_XV*). 251

In general, the frequency of SO clusters (and sequences) for each SG reflects the number of 252

copies in the LCAA (Table I, Fig. 5). On the other hand, only eleven of the 20 subgroups 253

were represented in UP clusters (SG_I*, SG_III*, SG_VI*, SG_VIII-2, SG_IX, SG_Xa, 254

SG_Xb*, SG_XI*, SG_XIIa, SG_XIIb, SG_XIIIa) and these SGs harbor a total of 837 255

sequences. SG_I*, SG_VIII-2, SG_XIIa, and SG_XIIb are clearly over-represented which is 256

in accordance with their expansion pattern. Other expanded SGs, however, have only a low 257

number of UP clusters or – in the case of SG_IV – no UP clusters at all. Therefore, it seems 258

that recently duplicated genes are more prone to be retained in some SGs. 259

260



16

Differences of selective constraint between subgroups, domains, and amino acids 261

To provide further insight into the LRR-RLK gene family evolution, we wanted to determine 262

under which kind of selective pressures the LRR-RLK genes evolved. We focused on the 263

dataset described above, i.e. LSE and orthologous genes. We inferred the dN/dS -ratio (or ω, 264

i.e. the ratio of non-synonymous vs. synonymous substitutions rates) at codons of the 265

alignments and branches of the phylogeny of the UP and SO clusters. An ω=1 indicates 266

neutral evolution/relaxed constraint, an ω<1 indicates purifying selection, and an ω>1 can 267

indicate positive selection. We used mapNH (Dutheil et al., 2012; Romiguier et al., 2012) to 268

compute the ω for each branch. mapNH ran for 71 UP and 176 SO clusters containing 1,246 269

and 2,960 branches, respectively (Table IV). We first wanted to test for relaxation of selective 270

constraint in UP and SO clusters and looked for branches with ω>1. We found 6.04% of UP 271

branches but only 0.49% of SO branches to have an ω>1. The mean ω for branches with ω>1 272

is significantly larger in UP clusters (1.45) compared to SO clusters (1.13, p=0.004). The 273

same is true for branches with ω<1 where ω is significantly larger in UP clusters (0.48) 274

compared to SO clusters (0.24, p<0.001). Overall, the mean ω is significantly larger for 275

branches from UP clusters (0.54) than for SO clusters (0.24, p<0.001) (Table IV, 276

Supplemental Fig. S2). 277

We found 38 out of 75 UP clusters (= 50.67%) containing codons under positive 278

selection (see Supplemental Table SIII for more details) after manual curation but only six out 279

of 186 SO clusters (= 3.23%). Additionally, codons under positive selection found in UP 280



17

clusters are not distributed evenly over domains (Fig. 6). To account for differences in domain 281

size, a hit frequency, i.e. the number of sites under positive selection we found relative to all 282

sites possible for each domain, was calculated (see Materials and Methods). The domain 283

showing the highest hit frequency is the LRR domain, followed by the cysteine-pairs and their 284



18

flanking regions (Fig. 6A). Hits in both domains are distributed over all SGs and species 285

tested. The KD and its surrounding domains contain very few codons under positive selection. 286

Domains classified as “other” combine domains important for the function of the LRR-RLK 287

genes but vary between SGs. For example, SG_I* (Fig. 6B) contains a malectin domain. All 288

hits classified as “other” here fall in the malectin-like domain (MLD) of a POPTR SG_I* 289

cluster. 290

Finally, we wanted to investigate whether some AAs in the LRR are more frequently 291

targeted by positive selection. The LRR typically contains 24 AAs and sometimes islands 292

between them (Fig. 6C). Four AAs were predominantly subject to positive selection: 6, 8, 10, 293

and 11 which all lie in the LRR-characteristic LXXLXLXX β-sheet/β-turn structure. 294

295

296

297



19

DISCUSSION 298

We studied the SG- and species-specific expansion dynamics in LRR-RLK genes from 31 299

angiosperm genomes in a phylogenetic framework. We also analyzed the lineage-specifically 300

expanded genes in this family to determine to which extent positive selection occurred on 301

them using a dN/dS-based test. We found differences in expansion patterns depending on SGs 302

and species but only a few SGs that were subjected to LSE. A significantly higher proportion 303

of LSE LRR-RLK genes was affected by positive selection compared to single-copy genes 304

and the LRR domain (specifically four AAs within this domain) were targeted by positive 305

selection. In the following, we will discuss our findings in more detail. 306

307

Subgroup- and species-specific expansions 308

We observed significant variations in the global expansion rates between LRR-RLK SGs. 309

These are due to a complex history of expansion-retention-loss cycles that are specific to each 310

SG. The phylogenetic approach allowed us to determine the relative importance of ancestral 311

versus recent species-specific expansions for each SG and to characterize precisely the 312

loss/retention dynamics along evolutionary history of the studied species (summarized in Fig. 313

4). For example, SG_III* and SG_XI* had a high copy number of LRR-RLK in the LCAA 314

and kept a stable copy number over the last 150 million years. On the other hand, SG_I*, 315

SG_XIIa, and SGXIIb, which had a moderate copy number in the LCAA, keep expanding. 316

Some functions have been described for genes of these SGs, mainly in A.thaliana 317

(Supplemental Table SIV). For SG_III* and SG_XI*, mostly genes involved in development 318

are described. The high numbers of ancestral genes in these two SGs combined with their size 319

stability during angiosperm evolution may be interpreted as an early high level of 320

diversification/specialization of these genes which are needed to orchestrate common 321

developmental features. This hypothesis can be reinforced by the high number of 322

superorthologous genes in these subgroups. For SG_I* and SG_XIIa, on the other hand, 323

mostly genes involved in response to biotic stress are described up to now. These observations 324

confirm that different expansion/retention patterns appear to be related to gene function 325

although one has to keep in mind that functions have only been assigned to few LRR-RLK 326

genes. Three SGs (SG_IX, SG_Xa, and SG_XIV) expanded compared to their very low 327

ancestral number (1-3) leading to a high total expansion rate. As it has been postulated that 328

duplications are the raw material for adaptation (Nei and Rooney, 2005; Fischer et al., 2014), 329

the evolution of those SGs was likely driven by adaptation – to varying degrees in different 330

angiosperm species, depending on the environment they evolved in. The known functions are 331



20

both related to response to biotic or abiotic stress and development. Because so far our 332

knowledge of LRR-RLK functions is limited and mostly restricted to A. thaliana, further 333

studies are needed to make more reliable statements on the link between function and 334

expansion/retention dynamics in different SGs. 335

Next, we wanted to ascertain species-specific expansions of LRR-RLK genes and how 336

they are related to the recent history of the species in our study. Whole genome multiplication 337

has been argued to be a major force in diversification of angiosperms (Soltis et al., 2009; 338

Soltis and Burleigh, 2009; Renny-Byfield and Wendel, 2014). All angiosperms share two 339

ancient WGDs (Jiao et al., 2011). Likewise, all monocots share a WGD ~130 Mya (Tang et 340

al., 2010a) and most dicots (Eudicots) share a WGT around the same time (Jaillon et al., 341

2007; Wang et al., 2012), but more recent WGDs and WGTs occurred in many angiosperm 342

species (Fig. 4, Table III). The link between WGD/Ts and the number of LRR-RLK genes is 343

not straightforward. We found that in Glycine max, Gossypium raimondii, and Malus x 344

domestica, which were subject to relatively recent WGDs (15-13, 17-13 and 45-30 Mya, 345

respectively) (Pfeil et al., 2005; Velasco et al., 2010; Wang et al., 2012), the number of LRR-346

RLK genes expanded more than 2-fold compared to the LCAA. These results are in 347

accordance with what was already described for these species. Indeed, it was found that G. 348

max contains a very large number of retained genes from this WGD (Cannon et al., 2014). 349

Additionally, recent studies on large gene families in G. raimondii indicate that their copy 350

number is either driven by retention after the last WGD (e.g. NAC transcription factors) 351

(Shang et al., 2013) or a combination of segmental (SD) and tandem duplications (TD) (e.g. 352

WRKY transcription factors) (Dou et al., 2014). For M. domestica (most recent WDG after 353

the divergence for peach according to Verde et al. (2013)), a recent study on nucleotide 354

binding site (NBS) LRR genes showed that they also stem mostly from SDs and TDs (Arya et 355

al., 2014). 356

More contrasted results are observed in Brassicaceae where two WGDs occurred (Barker 357

et al., 2009; Fawcett et al., 2009). Most SGs expand their number of genes on this ancestral 358

branch, but the species belonging to this clade mostly retain or loose genes on average (Fig. 2 359

and 4). The only exception concerns Eutrema salsugineum (an A. thaliana relative) which is 360

the only species with a more than 2-fold average expansion rate. The global expansion rate in 361

E. salsugineum is mostly due to two SGs (SG_I* and SG_XIIIa). In the original genome 362

paper (Wu et al., 2012), the authors found that genes from the category “response to stimulus” 363

(response to salt stress, osmotic stress, water deprivation, ABA stimulus, and hypoxia) are 364

significantly over-represented in E. salsugineum compared to A. thaliana. This over-365



21

representation is described as mostly caused by SDs and TDs (Wu et al., 2012) in accordance 366

with what we observed in SG_XIIIa. This could be of functional importance to this halophile 367

plant. 368

Finally, of all species analyzed here, Zea mays and Brassica rapa (and maybe Manihot 369

esculenta) show the most recent cases of WGD/T (12-5 and 9-5 Mya, respectively) (Schnable 370

et al., 2011; Wang et al., 2011) yet their expansion rates are moderate. This is further evidence 371

for the dynamic nature of angiosperm genomes that has been discussed before (Leitch and 372

Leitch, 2012; Fischer et al., 2014). After a WGD event, genomes tend to return to the diploid 373

(or previous) state by losing redundant duplicated genes (fractionation process) – although the 374

gene loss is biased (Bowers et al., 2003; Schnable et al., 2009). Which genes are lost or 375

retained strongly depends on their function (De Smet et al., 2013). However, it has been 376

shown that genes involved in stress response are mostly created by TDs rather than WGD 377

(Hanada et al., 2008). Indeed, it was hypothesized before that RLK genes involved in stress 378

response mostly duplicate by TD (Shiu et al., 2004). Here, we provide a detailed 379

representation of expansion-retention-loss dynamics of the whole LRR-RLK gene family in 380

31 angiosperm species (Fig.4). Each new genome sequenced will improve the accuracy of the 381

expansion-retention-loss event predictions and will help identifying new elements that can be 382

useful for future functional analysis and/or linked to adaptive traits. 383

384

Studying selection pressures in a large and dynamic gene family 385

As described above, the composition of LRR-RLKs in each of the 31 studied angiosperm 386

species results from a complex dynamic of species- and SG-specific expansion/loss events. To 387

further investigate the potential role of this family in plant adaptation we analyzed to which 388

selective pressures the LRR-RLKs were submitted. Such an analysis cannot be considered for 389

the phylogeny of the entire gene family because of the high number of sequences and high 390

sequence divergence (the phylogeny on which we divided the SGs was inferred on the 391

conserved kinase domain only). We then chose to focus on two specific cases: (i) LSE as a 392

specific case of duplication/retention, and (ii) a subset of strictly orthologous genes. Indeed, 393

LSE has been shown to fuel adaptation in angiosperms (Fischer et al., 2014) and we wanted to 394

test the prevalence of this mode of duplication in our large dataset. Therefore, we evaluated to 395

which extant LRR-RLK genes were subject to LSE and how positive selection acted on those 396

genes. As a reference, we chose the strictly orthologous subset. This approach allows the 397

interpretation of LSE evolution compared to the general LRR-RLK selective background 398

(Fischer et al., 2014). 399



22

The power of this phylogenetic approach relies on the number of species analyzed and we 400

profit from an ever increasing number of sequenced plant genomes. Another important 401

requirement for this approach is the quality of sequencing and annotation – especially for a 402

large gene family – as sequencing errors and mis-annotations can lead to false positives when 403

testing for positive selection (Han et al., 2013). We profit from a recently developed pipeline 404

designed to automatically perform different steps of the analysis (Fischer et al., 2014). This 405

allowed us to quickly incorporate sequenced genomes of choice and future studies can easily 406

expand this analysis as new reliable data becomes available. Finally, we set great value on 407

manually verifying the data throughout the process – from the identification of the LRR-408

RLKs to the inference of positive selection. Although this is tedious work for such a large 409

dataset, it is nevertheless important. As we recently showed, ~50% automatically reported 410

instances of positive selection turned out to be false positives after manual curation (Fischer et 411

al., 2014). 412

We found that all SGs are represented in the single-copy reference set with an over-413

representation of SG_III* and SG_XI*. This is in accordance with the fact that these two SGs 414

had the highest number of copies in the genome of the LCAA and did not significantly 415

expand since (see above). In general, the frequency of clusters from the single-copy gene set 416

(and sequences) for each SG reflects the number of copies in the LCAA (Table I, Fig. 5). On 417

the other hand, only eleven of the 20 SGs were represented in the LSE dataset. This is mainly 418

because the majority of expansions are rather old in these SGs, whereas they happened 419

relatively recently in SG_I*, SG_VIII-2, SG_XIIa, and SG_XIIb (see above). Fourteen 420

species (or clades) are represented in the LSE dataset: MUSAC (2 ultraparalog clusters), 421

SETIT (1), ORYZA (10), VITVI (3), SOLAN (6), MEDTR (3), GLYMA (2), PRUPE (6), 422

MALDO (11), POPTR (8), BRASS (11), GOSRA (5), THECC (2), and PHYPA (5). Again, 423

not every species is affected to the same extent, but this does not necessarily reflect recent 424

WGD/T. Additionally, LSE can also arise from SD and TD which frequency of occurrence is 425

not uniform within or between genomes. Our results indicate that different species are more 426

prone to retain recently duplicated genes than others. This in turn might reflect on their recent 427

evolution or domestication which should be examined in more detail in future studies. 428

When focusing on the study of selective pressures, we first looked at ω at the branches of 429

the LSE and single-copy gene clusters and found that selective constraint was relaxed in the 430

LSE dataset. This outcome was expected as it was previously shown that LSE genes evolve 431

more relaxed constraint than single-copy genes in angiosperms (Fischer et al., 2014). This 432

study, however, looked at whole angiosperm genomes but a similar pattern has already been 433



23

demonstrated in other large gene families (e.g. Johnson and Thomas, 2007; Xue et al., 2012; 434

Yang et al., 2013a; Yang et al., 2013b) and in LRR-RLK genes in particular (Tang et al., 435

2010b). Previous studies on that subject only had a limited dataset (four angiosperm species; 436

Tang et al. 2010b). Here, we demonstrate that this is still true when a larger and more 437

representative sample of angiosperms is considered. 438

Next, we wanted to identify codons which evolved under positive selection in the LSE 439

and the single-copy dataset. A recent study on gene families in the whole genomes of ten 440

angiosperms found that 5.4% of LSE genes contained codons showing positive selection 441

footprints (Fischer et al., 2014). Here, we ask if and to what extend this is also true for the 442

large and dynamic LRR-RLK gene family. We discovered that for LSE LRR-RLK genes, the 443

rate of codons under selection is almost 10-fold higher (50.67%) than the genome average. In 444

addition, we found >3% of single copy genes containing codons under selection whereas 445

Fischer et al. (2014) described no case of positive selection at the single-copy gene clusters in 446

their study. Together with the high rate of branches with ω>1 in LSE gene clusters (6.04%, 447

compared to 0.49% for single-copy genes) this indicates that LRR-RLK genes are more prone 448

to evolve under positive selection than the average of angiosperm gene families. As it might 449

be expected, all ultraparalog clusters with codons under positive selection come from the four 450

over-represented SGs: SG_I* (1 ultraparalog cluster), SG_VIII-2 (3), SG_XIIa (24), and 451

SG_XIIb (10). The single-copy gene clusters with codons under selection come from six SGs: 452

SG_III, SG_VIIa, SG_Xa, SG_Xb, SG_XIIa, and SG_XIIb. Therefore, recent expansion and 453

retention only affect a few SGs but in those SGs positive selection plays an important role. 454

For SG_XIIa, positive selection has been already previously inferred for genes involved in 455

environmental interactions: Xa21, which confers resistance to the bacterial blight disease, was 456

found to have evolved under positive selection in rice (Wang et al., 1998; Tan et al., 2011); 457

and FLS2, involved also in response to biotic stress, shows a signature of rapid fixation of an 458

adaptive allele in Arabidopsis (Vetter et al., 2012). Future studies on smaller subsets of SGs 459

will surely cast further light on selection patterns in LRR-RLK genes. Only eleven species (or 460

clades) are represented in the LSE dataset with codons under positive selection: SETIT (1 461

ultraparalog cluster), ORYZA (2), SOLAN (4), MEDTR (2), GLYMA (2), PRUPE (3), 462

MALDO (8), POPTR (7), BRASS (2), GOSRA (5), and THECC (2). Not every species is 463

affected the same level by positive selection and again future studies might bring more details 464

concerning the evolutionary history of specific species and SGs to light. 465

In addition, we found that not every domain of the LRR-RLK genes was similarly 466

affected by positive selection. Most codons under selection fall in the LRR domain. This 467



24

outcome might be expected as LRRs are very dynamic and plasticity in this region provides 468

plants with a broad toolset to face environmental challenges and therefore undergoes positive 469

selection frequently (Zhang et al., 2006; Tang et al., 2010b). Only very few codons under 470

positive selection were found in the kinase domain and its surrounding regions. This result is 471

consistent with the fact that the KD is very conserved among species and SGs and evolved 472

mostly under purifying selection (Shiu et al., 2004; Tang et al., 2010b). A more surprising 473

result was the identification of a significant number of positively selected sites in the 474

malectin-like domain of a Populus trichocarpa SG_I* cluster. So far, the function of 475

extracellular malectin-like domains of RLKs is not well understood (Lindner et al., 2012). 476

However, a malectin-like domain-containing SG_I* LRR-RLK has been described to confer 477

susceptibility to a downy mildew pathogen in A. thaliana and to have similarities to 478

Symbiosis RLKs (SYMRKs) which are important for the regulation of bacterial symbiont 479

accommodation (Markmann et al., 2008; Hok et al., 2011). Therefore, our results suggest that 480

it could be interesting to further investigate the function and evolutionary history of this 481

SG_I* domain, particularly in P. trichocarpa. Another unexpected finding was the frequent 482

occurrence of positive selection at the cys-pairs and flanking regions which are involved in 483

folding and/or the binding to other proteins. To what extent the function of LRR-RLKs is 484

affected by mutations in the cys-pair regions depends on the function of the gene (Song et al., 485

2010; Sun et al., 2012) and it would be interesting to study this in more detail in the future. 486

Finally, we took a closer look at the AAs in the LRR primarily affected by positive 487

selection. Only four, out of the 24 AAs a LRR typically contains, were predominantly and 488

strongly subject to positive selection. These variable AAs lie in the un-conserved part of the 489

LRR-characteristic LXXLXLXX β-sheet/β-turn structure which is involved in protein-protein 490

interactions (Jones and Jones, 1997; Enkhbayar et al., 2004). Specifically, solvent-exposed 491

residues were targeted by positive selection (Parniske et al., 1997; Wang et al., 1998). Further 492

investigation on the functional consequences of these nucleotide variations need to be done to 493

confirm their adaptive potential but our findings align very well to the current understanding 494

of LRR ligand binding. Taken together, our results could be very useful for further functional 495

investigations of LRR-RLK genes in different species. 496

497

498

CONCLUSIONS 499

We studied LRR-RLK genes from 33 land plant species to investigate SG- and species-500

specific expansion of these genes, to which extent they were subject to LSE, and to determine 501



25

the role positive selection played in the evolution of this large gene family. We described that 502

some SGs are more prone to expansion/retention than others and that the expansions occurred 503

at different times in the evolution of LRR-RLK genes. This fine-scale analysis of the dynamic 504

allowed us to identify branches and species for which a higher than average retention rate 505

could indicate a potential adaptive event for some SGs. We also described that only a few SGs 506

show patterns of recent LSE and that at those genes selective constraint is relaxed. More than 507

50% of the LSE genes contain codons which show evidence for positive selection which is 508

almost 10-fold the frequency previously described at gene families in angiosperms (Fischer et 509

al., 2014). Finally, we found that over the LRR-RLK genes the LRR domain and specifically 510

four AAs responsible for ligand interaction are most frequently subject to selection. 511

512

513

MATERIALS AND METHODS 514

Studied Genomes 515

We analyzed 31 angiosperm genomes (eight monocot (sub)species and 23 dicot species) (see 516

Table II): Phoenix dactylifera (Al-Dous et al., 2011), Musa acuminata (D'Hont et al., 2012), 517

Oryza sativa subsp. japonica (International Rice Genome Sequencing Project, 2005), Oryza 518

sativa subsp. indica (Yu et al., 2002), Brachypodium distachyon (The International 519

Brachypodium Initiative, 2010), Zea mays (Schnable et al., 2009), Sorghum bicolor (Paterson 520

et al., 2009), Setaria italica (Zhang et al., 2012), Solanum tuberosum (Potato Genome 521

Sequencing Consortium, 2011), Solanum lycopersicum (The Tomato Genome Consortium, 522

2012), Vitis vinifera (Jaillon et al., 2007), Lotus japonicus (Sato et al., 2008), Cajanus cajan 523

(Varshney et al., 2012), Arabidopsis thaliana (The Arabidopsis Genome Initiative, 2000), 524

Arabidopsis lyrata (Hu et al., 2011), Schrenkiella parvula (a synonym is Eutrema parvula, we 525

used the nomenclature from Oh et al. (2014)) (Dassanayake et al., 2011), Eutrema 526

salsugineum (a synonym is Thellungiella halophila, we chose the nomenclature according to 527

phytosome: http://phytozome.jgi.doe.gov/pz/portal.html#!info?alias=Org_Esalsugineum) (Wu 528

et al., 2012), Brassica rapa (Wang et al., 2011), Populus trichocarpa (Tuskan et al., 2006), 529

Glycine max (Schmutz et al., 2010), Medicago truncatula (Young et al., 2011), Prunus 530

persica (Ahmad et al., 2011), Malus x domestica (Velasco et al., 2010), Ricinus communis 531

(Chan et al., 2010), Jatropha curcas (Sato et al., 2011), Manihot esculenta (Prochnik et al., 532

2012), Cucumis sativus (Huang et al., 2009), Cucumis melo (Garcia-Mas et al., 2012), Carica 533

papaya (Ming et al., 2008), Gossypium raimondii (Wang et al., 2012), and Theobroma cacao 534

(Argout et al., 2011). We also extracted LRR-RLKs from the moss Physcomitrella patens 535



26

(Rensing et al., 2008) and the spikemoss Selaginella moellendorffii (Banks et al., 2011). 536

Throughout the article we refer to the species using five-digit identifiers which can be found 537

in Table II. Altogether, we analyzed 33 genomes from 39 proteomes (we used several 538

annotation versions of the A. thaliana and O. sativa genomes). A table containing the details 539

on which genome versions we used can be found in Supplemental Table SV. The phylogeny 540

of those species is provided in Fig. 4. 541

542

LRR-RLK extraction, clustering, phylogeny, and identification of gain/loss events 543

We used the hmmsearch program (Eddy, 2009) to extract peptide sequences containing both, 544

intact (i.e. non-degenerated) LRR(s) and a KD from the proteomes as previously described by 545

(Dievart et al., 2011). We classified SGs using the KD by a global phylogenetic analysis (the 546

tree can be found at http://phylogeny.southgreen.fr/kinase/index.php - Global Analysis). First, 547

sequences were aligned using MAFFT (Katoh et al., 2005) with a progressive strategy. 548

Second, the alignments were cleaned using TrimAl (Capella-Gutiérrez et al., 2009) with 549

settings to remove every site with more than 20% of gaps or with a similarity score lower than 550

0.001. Third, a similarity matrix was computed by ProtDist (Felsenstein, 1993) using a JTT 551

model. Fourth, a global distance phylogeny was inferred using FastME (Desper and Gascuel, 552

2006) with default settings and SPR movements to optimize the tree topology. Fifth, SGs 553

were defined manually in the global phylogeny using the Arabidopsis genes as reference 554

which lead us to 20 SGs in contrast to the 15 previously described (Shiu et al., 2004; Lehti-555

Shiu et al., 2009). 556

More accurate phylogenies were then inferred for each of the 20 SGs. The KD of the 557

sequences attributed to each SG were re-aligned using MAFFT with an iterative strategy 558

(maximum of 100 iterations). Alignments were cleaned using TrimAl with settings to only 559

remove sites with more than 80% of gaps. Then, maximum likelihood phylogenies were 560

inferred by PhyML 3.0 (Guindon et al., 2010) using a LG+gamma model and the best of NNI 561

and SPR topology optimization. Statistical branch support was computed using the aLRT/SH-562

like strategy (Guindon et al. 2010). This left us with 20 phylogenies, one for each SG (all 563

phylogenies are available at http://phylogeny.southgreen.fr/kinase/index.php - SG_I - 564

SG_XV). 565

Each of the 20 phylogenetic trees has been reconciled with the species tree using RAP-566

Green (Dufayard et al., 2005; https://github.com/SouthGreenPlatform/rap-green). By 567

comparing the gene tree to the species tree, this analysis allows to root phylogenetic trees and 568

to infer duplication and loss events (Dufayard et al., 2005). We tested this approach of rooting 569



27

(by minimizing the number of inferred duplications and losses) and compared it to rooting 570

with outgroups (data not shown). The two methods provided very close root locations that did 571

not change the overall conclusions. Using this RAP-Green tree reconciliation approach 572

(parameters: Maximum support for reduction 0.95), we inferred the number of duplications 573

and losses at each node of the species tree. Briefly, each duplication and loss respectively 574

increases and decreases by one the number of copies in the common ancestor of the 575

taxonomic group analyzed. 576

We determined the global SG- and species-specific expansion rate by computing the 577

number of LRR-RLK genes in one SG divided by the ancestral number and number of LRR-578

RLK genes in one species divided by the ancestral number, respectively. An ANOVA 579

analysis showed that the expansion rate differed significantly between the SGs/species (p<2e-580

16 in both cases). We used the TukeyHSD test of the agricolae package (http://cran.r-581

project.org/web/packages/agricolae/index.html) in R (R Development Core Team, 2012) to 582

further explore which groups of SGs/species differ from each other. This test compares the 583

range of sample means and defines an Honest Significance Difference (HSD) value which is 584

the minimum distance between groups to be considered statistically significant. In short, 585

TukeyHSD is a post-hoc test which groups subsets by significance levels after ANOVA 586

showed significant differences between subsets. 587

588

LSE dataset and testing for positive selection 589

Testing for adaptation can be done by comparing positive (Darwinian) selection footprints in 590

lineages with recently and specifically duplicated genes to reference lineages containing only 591

single-copy genes. One way to infer positive selection is by analyzing nucleotide substitution 592

data at the codon level in a phylogenetic framework. As nucleotide substitutions can either be 593

nonsynonymous (i.e. protein changing, thereby potentially impacting the fitness) or 594

synonymous (i.e. not protein changing, thereby theoretically without consequences for the 595

fitness, but see (Lawrie et al., 2013)), the nonsynonymous/synonymous substitution rate ratio, 596

denoted as dN/dS or ω, can be used to infer the direction and strength of natural selection. An 597

ω<1 indicates purifying selection and the closer ω is to 0, the stronger purifying selection is 598

acting. Under neutral evolution, ω=1. An ω>1 indicates that positive selection is acting. 599

We identified ultraparalog clusters (UP – only related by duplication) using a tree 600

reconciliation approach (Dufayard et al., 2005). Those represent our LSE gene set. As a 601

single-copy gene reference, we chose a superortholog gene set (SO – only related by 602

speciation). We chose clusters with a minimum of five sequences. To address the question of 603



28

whether or not positive selection is more frequent after LSE events, we compared the results 604

obtained on UPs with those obtained on SO gene sets. Species which diverged <15 Mya were 605

merged for the LSE detection (see Fig. 4) in order not to overly reduce the ultraparalog (UP) 606

dataset and to not induce bias due to very recent speciation events: ANDRO (= ZEAMA and 607

SORBI), ORYZA (= ORYSJ and ORYSI), SOLAN (= SOLLC and SOLTU), CUCUM (= 608

CUCSA and CUCME), BRASS (= ARATH, ARALY, BRARA, SCHPA and EUTSA). We 609

then applied the pipeline developed by Fischer et al. (2014) to the extracted UP and SO 610

clusters. In short, the pipeline consists of following steps: (i) The clusters were aligned using 611

PRANK+F with codon option (Löytynoja and Goldman, 2005). The alignments were cleaned 612

by GUIDANCE (Penn et al., 2010) with the default sequence quality cut-off and a column 613

cut-off of 0.97 to remove problematic sequences and unreliable sites from the alignments. We 614

used PRANK and GUIDANCE here as previous benchmarks (Fletcher and Yang, 2010; 615

Jordan and Goldman, 2012) showed that these programs lead to a minimum of false positives 616

when inferring positive selection using codeml. The cleaned alignments can be retrieved here: 617

http://phylogeny.southgreen.fr/kinase/alignments.php – Alignments: Manually curated 618

alignments for positive selection analysis. (ii) We relied on the egglib package (De Mita and 619

Siol, 2012) to infer the maximum likelihood phylogeny at the nucleotide level for every 620

alignment using PhyML 3.0 (Guindon et al., 2010) under the GTR substitution model. (iii) 621

We ran the codeml site model implemented in the PAML4 software (Yang, 2007) to infer 622

positive selection on codons under several substitution models. In clusters identified to have 623

evolved under positive selection, Bayes empirical Bayes was used to calculate the posterior 624

probabilities at each codon and detect those under positive selection (i.e. those with a 625

posterior probability of ω>1 strictly above 95%). All alignments detected to be under positive 626

selection at the codon level were curated manually for potential alignment errors. A table 627

containing the details on all codons showing a signal of positive selection using codeml can 628

be found in Supplemental Table SIII. (iv) We used mapNH (Dutheil et al., 2012; Romiguier et 629

al., 2012) to infer ω at the branch level. 630

In order to analyze the distribution of positively selected sites among domains, we 631

calculated a hit frequency that computes the number of sites under positive selection found in 632

each domain relative to all sites possible. All possible sites for each domain were calculated 633

as follows: First, we extracted the size of each domain of every SG. If SGs were subdivided 634

further we took the average size of each domain. Second, we multiplied the size of each 635

domain by the number of UP clusters we found for each SG. For example: the LRR of SG_I* 636

contains an average of 77 sites. We found 8 UP clusters for SG_I*. Therefore, the total 637



29

number of possible LRR sites for SG_I* is 77*8=616 sites. Third, we added the sites for each 638

domain up for all SGs. 639



30

SUPPLEMENTAL DATA 640

Supplemental Tables SI – SV can be obtained from: 641

http://phylogeny.southgreen.fr/kinase/index.php - Tables 642

Supplemental Table SI: Estimated divergence times and corresponding references for Fig. 4. 643

Supplemental Table SII: Results of the TukeyHSD test. 644

Supplemental Table SIII: Details on all codons showing a signal of positive selection using 645

codeml. 646

Supplemental Table SIV: Arabidopsis LRR-RLK gene classification according to TAIR 647

(https://www.arabidopsis.org/) 648

Supplemental Table SV: List of genomes used here, with name, link, and version of the 649

genome fasta file. 650

Supplemental Figure S1: Summary of ultraparalog and superortholog cluster size and 651

length. 652

Each dot represents (A) an ultraparalog or (B) a superortholog alignment. The histogram 653

above the scatter plot represents the count of alignments for each cluster size (= number of 654

sequences in alignment); the histogram right to the scatter plot represents the frequency of 655

alignments for each alignment length. 656

Supplemental Figure S2: ω distribution of branches of UP and SO clusters. 657

The distribution of ω of branches in UP (purple) and SO clusters (yellow). 658

659

660

ACKNOWLEGEMENTS 661

The authors thank the reviewers for their helpful comments. 662



31

Table I: Total number of LRR-RLK in our angiosperm dataset, number of ancestral genes in 663

LCAA, and median global expansion rate for each SG among the 31 species. 664

SG Total number

of genes Number of

ancestral genes Median global expansion rate

I* 482 7 2.00 II 349 9 1.22

III* 1,400 32 1.22 IV 131 3 1.33 V 263 5 1.80

VI* 324 10 1.00 VIIa 157 3 1.67 VIIb 84 2 1.50

VIII-1 216 5 1.40 VIII-2 355 8 1.25

IX 193 3 1.67 Xa 143 2 2.00

Xb* 367 9 1.11 XI* 1,177 29 1.28 XIIa 1,126 9 3.00 XIIb 423 4 2.00 XIIIa 84 2 1.50 XIIIb 77 2 1.00 XIV 84 1 3.00 XV* 119 5 0.80 Total 7,554 150

665



32

Table II: Five-digit code for each species. 666

Species name Common name Five-digit code Phoenix dactylifera Date palm PHODC

Musa acuminata Banana MUSAC

Brachypodium distachyon Purple false brome BRADI

Oryza sativa ssp. japonica Asian rice ORYSJ

Oryza sativa ssp. indica Indian rice ORYSI

Setaria italica Foxtail millet SETIT

Zea mays Maize MAIZE

Sorghum bicolor Milo SORBI

Solanum tuberosum Potato SOLTU

Solanum lycopersicum Tomato SOLLC

Vitis vinifera Common grape vine VITVI

Theobroma cacao Cacao tree THECC

Gossypium raimondii Cotton progenitor GOSRA

Carica papaya Papaya CARPA

Arabidopsis thaliana Thale cress ARATH

Arabidopsis lyrata Out-crossing ARATH relative ARALY

Brassica rapa Turnip BRARA

Schrenkiella parvula A saltwater cress SCHPA

Eutrema salsugineum A saltwater cress EUTSA

Cucumis sativus Cucumber CUCSA

Cucumis melo Melon CUCME

Prunus persica Peach PRUPE

Malus x domestica Apple MALDO

Lotus japonicus LOTJA

Medicago truncatula Barrel medic MEDTR

Glycine max Soybean GLYMA

Cajanus cajan Pigeon pea CAJCA

Populus trichocarpa Black cottonwood POPTR

Ricinus communis Castor oil plant RICCO

Jatropha curcas Barbados nut JATCU

Maniohot esculenta Cassava MANES

Selaginella moellendorffii A spikemoss SELML

Physcomitrella patens A moss PHYPA

667



33

Table III: Polyploidy events Estimated times of polyploidy event and corresponding 668

references for Fig. 4. 669

Event Name Reference Age [million years]

1 Seed plant tetraploidy (Jiao et al., 2011) 350-330

2 Angiosperm tetraploidy (Jiao et al., 2011) 230-190

3 Monocot tetraploidy (Tang et al., 2010a) 130

4 Date palm WGD (D'Hont et al., 2012) 75-65 (?)

5 Banana gamma (D'Hont et al., 2012) 100

6 Banana beta (D'Hont et al., 2012) 65

7 Banana alpha (D'Hont et al., 2012) 65

8 Grass tetraploidy B (sigma) (D'Hont et al., 2012) 123-109

9 Grass tetraploidy (rho) (Paterson et al., 2004) 70

10 Maize tetraploidy (Schnable et al., 2011) 12-5

11 Eudicot hexaploidy

(Arabidopsis gamma)

(Jaillon et al., 2007; Cenci et

al., 2010; Wang et al., 2012) 150-120

12 Solanum hexaploidy (The Tomato Genome

Consortium, 2012) 91-52

13 Papiloniod tetraploidy (Pfeil et al., 2005) 55-54

14 Soybean tetraploidy (Pfeil et al., 2005) 15-13

15 Apple tetraploidy (Velasco et al., 2010; Verde

et al., 2013) 45-30

16 Poplar tetraploidy (Tuskan et al., 2006) 65-60

17 Arabidopsis beta (Fawcett et al., 2009) 70-40

18 Arabidopsis alpha (Barker et al., 2009) 23

19 Brassica hexaploidy (Wang et al., 2011) 9-5

20 Cotton WGD (Wang et al., 2012) 20-13

21 Cassava WGD (Mühlhausen and Kollmar,

2013)

? (after

Crotonoideae split)

670

671



34

Table IV: Details of the LSE and mapNH analysis for UP and SO clusters. 672

UP SO

total number of clusters 75 189

clusters for final mapNH analysis 71 176

median cluster size (1st; 3rd Qu) 8 (6; 12) 8 (6; 14)

min; max cluster size 5; 38 5; 25

median alignment length (1st; 3rd Qu) 3,237

(2,952; 3,574)

2,841

(2,034; 3,192)

min; max alignment length 1,749; 8,691 861; 6,216

branches analyzed/total number of

branches

1,193/1,246 2,860/2,960

clusters with branches omega > 1.0 (%) 25 (35.21) 10 (5.68)

branches with omega < 1.0 (%) 1,121 (93.96) 2,846 (99.51)

mean omega for < 1.0 branches +/- sd 0.48 +/- 0.17 0.24 +/- 0.12

branches with omega > 1.0 (%) 72 (6.04) 14 (0.49)

mean omega for > 1.0 branches +/- sd 1.45 +/- 0.51 1.13 +/- 0.14

mean omega +/- sd 0.54 +/- 0.31 0.24 +/- 0.13

673

674



35

FIGURE LEGENDS 675

Figure 1: Global expansion rate in each subgroup: Total number of genes in each species 676

divided by the ancestral number (see Table I). An ANOVA test showed that the expansion 677

rate differs significantly between SGs (p<2e-16). Therefore, we performed a TukeyHSD test 678

to determine which SGs exactly show a significant difference between each other and group 679

those SGs by significance level (a-e). Letters above the boxplot indicate TukeyHSD 680

significance group (see Supplemental Table SII). The significance groups are color coded 681

according to the mean expansion rate: orange: >2.25 fold expansion; red: 1.75-2.25 fold 682

expansion; purple: 1.30-1.75 fold expansion; blue: 0.75-1.30 fold expansion (i.e. no 683

expansion). The outlier species are labeled for each SG. See Table II for species IDs. 684

685

Figure 2: Branch-specific expansion/diminution of LRR-RLK genes for every SG on every 686

branch in the phylogenetic tree. The tree on the left displays all the nodes and branches, 687

polyploidy events are marked with dots. Every line gives the expansion rate where the current 688

(descendant) node is compared to the previous (ascendant) node. Red boxes indicate 689

expansion, blue boxes indicate diminution, and blank boxes indicate stagnation. For example: 690

SG_I* has the same number of copies in monocots compared to the ascendant node (= 691

angiosperms) indicated by a blank box. In PHODC, a diminution occurred compared to the 692

ascendant node (= monocots) indicated by a blue box. In MUSAC, an expansion occurred 693

compared to the ascendant node (= monocots) indicated by a red box and so on. 694

695

Figure 3: Global expansion rate in each species: Total number of genes in each species 696

divided by the ancestral number (see Table I). An ANOVA test showed that the expansion 697

rate differs significantly between species (p<2e-16). Therefore, we performed a TukeyHSD 698

test to determine which species exactly show a significant difference between each other and 699

group those species by significance level (a-e). Letters above the boxplot indicate TukeyHSD 700

significance group (see Supplemental Table SII). The significance groups are color coded 701

according to the mean expansion rate: orange: >2.25 fold expansion; red: 1.75-2.25 fold 702

expansion; purple: 1.40-1.75 fold expansion; blue: 0.80-1.40 fold expansion (i.e. no 703

expansion). The outlier SGs are labeled for each species. See Table II for species IDs. 704

705

Figure 4: Phylogenetic tree of the 33 species studied here. Five-digit species identifiers are 706

given in parenthesis next to the species name. Species which diverged <15 mya were merged 707

for the LSE analysis (see Materials and Methods): ANDRO, ORYZA, SOLAN, CUCUM, 708



36

BRASS. Polyploidy events and their estimated ages are indicated on the tree: circles on the 709

branches represent WGD, dark circles represent WGT. The numbers in the circles refer to 710

details on the polyploidization events given in Table I. Species divergence and their estimated 711

age are indicated by grey squares on the nodes. The numbers in the squares refer to details on 712

the divergence times given in Supplemental Table SI. Dots and asterisks on the branches 713

indicate SG expansions. Dots, 2-fold; small asterisks, between 2 and 4-fold; large asterisks, 714

equal or more than 4-fold. SG I* (brown), SG_IV (dark green), SG_V (grey), SG_VIIa 715

(orange), SG_VIIb (yellow), SG_VIII-1 (dark brown), SG_VIII-2 (green), SG_IX (light blue), 716

SG_Xa (dark blue), SG_XIIa (pink), SG_XIIb (purple), SG_XIIIa (red), SG_XIV (black), 717

SG_XV* (white). The asterisks and dots do not indicate the exact age. 718

719

Figure 5: Distribution of UP and SO clusters and sequences over all SGs. Frequency of all 720

extracted UP (dark blue) and SO clusters (dark orange) for each SG; Frequency of all 721

extracted UP (light blue) and SO sequences (light orange) for each SG. 722

723

Figure 6: (A) Hit frequency (i.e. frequency of codons under selection vs. total number of 724

sites) for each domain of the LRR-RLK genes. (B) Schematic structure of the LRR-RLK 725

genes, here with SG_I* gene structure as an example. The absence/presence and size of the 726

domains varies between SGs, please see text for details. N-term, N-terminal end; SP (dark 727

grey), signal peptide; Cys-pair 1 (blue), first cysteine pair; NC1, N-terminal of Cys-pair 1; 728

CC1, C-terminal of Cys-pair 1; other (green), other domains; LRR (red), leucine-rich repeat; 729

Cys-pair 2 (blue), first cysteine pair; NC2, N-terminal of Cys-pair 2; CC2, C-terminal of Cys-730

pair 2; TM (black), trans-membrane domain; JM, juxta-membrane domain; KD (yellow), 731

kinase domain; C-term, C-terminal end; inter, other inter-domain regions. (C) Frequency of 732

amino acids in the LRR domain under positive selection. L, leucine; N, asparagine; G, 733

glycine; I, isoleucine; P, proline; x, variable; is, island between LRRs. 734



37

735



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Argout X, Salse J, Aury JM, Guiltinan MJ, Droc G, Gouzy J, Allegre M, Chaparro C, Legavre T, Maximova SN, Abrouk M, Murat F,Fouet O, Poulain J, Ruiz M, Roguet Y, Rodier-Goud M, Barbosa-Neto JF, Sabot F, Kudrna D, Ammiraju JS, Schuster SC, CarlsonJE, Sallet E, Schiex T, Dievart A, Kramer M, Gelley L, Shi Z, Berard A, Viot C, Boccara M, Risterucci AM, Guignon V, Sabau X, AxtellMJ, Ma Z, Zhang Y, Brown S, Bourge M, Golser W, Song X, Clement D, Rivallan R, Tahi M, Akaza JM, Pitollat B, Gramacho K,D'Hont A, Brunel D, Infante D, Kebe I, Costet P, Wing R, McCombie WR, Guiderdoni E, Quetier F, Panaud O, Wincker P, Bocs S,Lanaud C (2011) The genome of Theobroma cacao. Nat Genet 43: 101-108


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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Whole genome sequencing of peach Prunus persica L%2E for SNP identification and selection%2E%5BTitle%5D%29 AND Ahmad R%2C Parfitt D%2C Fass J%2C Ogundiwin E%2C Dhingra A%2C Gradziel T%2C Lin D%2C Joshi N%2C Martinez%2DGarcia P%2C Crisosto C%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Ahmad R, Parfitt D, Fass J, Ogundiwin E, Dhingra A, Gradziel T, Lin D, Joshi N, Martinez-Garcia P, Crisosto C (2011) Whole genome sequencing of peach (Prunus persica L.) for SNP identification and selection. BMC Genomics 12: 569

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http://scholar.google.com/scholar?as_q=Whole genome sequencing of peach (Prunus persica L.) for SNP identification and selection.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Biotechnol%5BTitle%5D%29 AND 29%5BVolume%5D AND 521%5BPagination%5D AND Al%2DDous EK%2C George B%2C Al%2DMahmoud ME%2C Al%2DJaber MY%2C Wang H%2C Salameh YM%2C Al%2DAzwani EK%2C Chaluvadi S%2C Pontaroli AC%2C DeBarry J%2C Arondel V%2C Ohlrogge J%2C Saie IJ%2C Suliman%2DElmeer KM%2C Bennetzen JL%2C Kruegger RR%2C Malek JA%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Al-Dous EK, George B, Al-Mahmoud ME, Al-Jaber MY, Wang H, Salameh YM, Al-Azwani EK, Chaluvadi S, Pontaroli AC, DeBarry J, Arondel V, Ohlrogge J, Saie IJ, Suliman-Elmeer KM, Bennetzen JL, Kruegger RR, Malek JA (2011) De novo genome sequencing and comparative genomics of date palm (Phoenix dactylifera). Nat Biotechnol 29: 521-527

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http://scholar.google.com/scholar?as_q=De novo genome sequencing and comparative genomics of date palm (Phoenix dactylifera)&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28J Biol Chem%5BTitle%5D%29 AND 285%5BVolume%5D AND 19035%5BPagination%5D AND Albert M%2C Jehle AK%2C Mueller K%2C Eisele C%2C Lipschis M%2C Felix G%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Albert M, Jehle AK, Mueller K, Eisele C, Lipschis M, Felix G (2010) Arabidopsis thaliana pattern recognition receptors for Bacterial Elongation Factor Tu and Flagellin can be combined to form functional chimeric receptors. J Biol Chem 285: 19035-19042

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Albert&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Arabidopsis thaliana pattern recognition receptors for Bacterial Elongation Factor Tu and Flagellin can be combined to form functional chimeric receptors&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Arabidopsis thaliana pattern recognition receptors for Bacterial Elongation Factor Tu and Flagellin can be combined to form functional chimeric receptors&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Albert&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Genet%5BTitle%5D%29 AND 43%5BVolume%5D AND 101%5BPagination%5D AND Argout X%2C Salse J%2C Aury JM%2C Guiltinan MJ%2C Droc G%2C Gouzy J%2C Allegre M%2C Chaparro C%2C Legavre T%2C Maximova SN%2C Abrouk M%2C Murat F%2C Fouet O%2C Poulain J%2C Ruiz M%2C Roguet Y%2C Rodier%2DGoud M%2C Barbosa%2DNeto JF%2C Sabot F%2C Kudrna D%2C Ammiraju JS%2C Schuster SC%2C Carlson JE%2C Sallet E%2C Schiex T%2C Dievart A%2C Kramer M%2C Gelley L%2C Shi Z%2C Berard A%2C Viot C%2C Boccara M%2C Risterucci AM%2C Guignon V%2C Sabau X%2C Axtell MJ%2C Ma Z%2C Zhang Y%2C Brown S%2C Bourge M%2C Golser W%2C Song X%2C Clement D%2C Rivallan R%2C Tahi M%2C Akaza JM%2C Pitollat B%2C Gramacho K%2C D%27Hont A%2C Brunel D%2C Infante D%2C Kebe I%2C Costet P%2C Wing R%2C McCombie WR%2C Guiderdoni E%2C Quetier F%2C Panaud O%2C Wincker P%2C Bocs S%2C Lanaud C%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Genome%2Dwide identification and expression analysis of NBS%2Dencoding genes in Malus x domestica and expansion of NBS genes family in Rosaceae%2E%5BTitle%5D%29 AND Arya P%2C Kumar G%2C Acharya V%2C Singh AK%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Arya P, Kumar G, Acharya V, Singh AK (2014) Genome-wide identification and expression analysis of NBS-encoding genes in Malus x domestica and expansion of NBS genes family in Rosaceae. PLOS ONE 9: e107987

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Arya&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Genome-wide identification and expression analysis of NBS-encoding genes in Malus x domestica and expansion of NBS genes family in Rosaceae.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Genome-wide identification and expression analysis of NBS-encoding genes in Malus x domestica and expansion of NBS genes family in Rosaceae.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Arya&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Science%5BTitle%5D%29 AND 332%5BVolume%5D AND 960%5BPagination%5D AND Banks JA%2C Nishiyama T%2C Hasebe M%2C Bowman JL%2C Gribskov M%2C dePamphilis C%2C Albert VA%2C Aono N%2C Aoyama T%2C Ambrose BA%2C Ashton NW%2C Axtell MJ%2C Barker E%2C Barker MS%2C Bennetzen JL%2C Bonawitz ND%2C Chapple C%2C Cheng C%2C Correa LGG%2C Dacre M%2C DeBarry J%2C Dreyer I%2C Elias M%2C Engstrom EM%2C Estelle M%2C Feng L%2C Finet C%2C Floyd SK%2C Frommer WB%2C Fujita T%2C Gramzow L%2C Gutensohn M%2C Harholt J%2C Hattori M%2C Heyl A%2C Hirai T%2C Hiwatashi Y%2C Ishikawa M%2C Iwata M%2C Karol KG%2C Koehler B%2C Kolukisaoglu U%2C Kubo M%2C Kurata T%2C Lalonde S%2C Li K%2C Li Y%2C Litt A%2C Lyons E%2C Manning G%2C Maruyama T%2C Michael TP%2C Mikami K%2C Miyazaki S%2C Morinaga Si%2C Murata T%2C Mueller%2DRoeber B%2C Nelson DR%2C Obara M%2C Oguri Y%2C Olmstead RG%2C Onodera N%2C Petersen BL%2C Pils B%2C Prigge M%2C Rensing SA%2C Ria�o%2DPach�n DM%2C Roberts AW%2C Sato Y%2C Scheller HV%2C Schulz B%2C Schulz C%2C Shakirov EV%2C Shibagaki N%2C Shinohara N%2C Shippen DE%2C S�rensen I%2C Sotooka R%2C Sugimoto N%2C Sugita M%2C Sumikawa N%2C Tanurdzic M%2C Thei�en G%2C Ulvskov P%2C Wakazuki S%2C Weng JK%2C Willats WWGT%2C Wipf D%2C Wolf PG%2C Yang L%2C Zimmer AD%2C Zhu Q%2C Mitros T%2C Hellsten U%2C Loqu� D%2C Otillar R%2C Salamov A%2C Schmutz J%2C Shapiro H%2C Lindquist E%2C Lucas S%2C Rokhsar D%2C Grigoriev IV%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Banks JA, Nishiyama T, Hasebe M, Bowman JL, Gribskov M, dePamphilis C, Albert VA, Aono N, Aoyama T, Ambrose BA, Ashton NW, Axtell MJ, Barker E, Barker MS, Bennetzen JL, Bonawitz ND, Chapple C, Cheng C, Correa LGG, Dacre M, DeBarry J, Dreyer I, Elias M, Engstrom EM, Estelle M, Feng L, Finet C, Floyd SK, Frommer WB, Fujita T, Gramzow L, Gutensohn M, Harholt J, Hattori M, Heyl A, Hirai T, Hiwatashi Y, Ishikawa M, Iwata M, Karol KG, Koehler B, Kolukisaoglu U, Kubo M, Kurata T, Lalonde S, Li K, Li Y, Litt A, Lyons E, Manning G, Maruyama T, Michael TP, Mikami K, Miyazaki S, Morinaga Si, Murata T, Mueller-Roeber B, Nelson DR, Obara M, Oguri Y, Olmstead RG, Onodera N, Petersen BL, Pils B, Prigge M, Rensing SA, Ria�o-Pach�n DM, Roberts AW, Sato Y, Scheller HV, Schulz B, Schulz C, Shakirov EV, Shibagaki N, Shinohara N, Shippen DE, S�rensen I, Sotooka R, Sugimoto N, Sugita M, Sumikawa N, Tanurdzic M, Thei�en G, Ulvskov P, Wakazuki S, Weng JK, Willats WWGT, Wipf D, Wolf PG, Yang L, Zimmer AD, Zhu Q, Mitros T, Hellsten U, Loqu� D, Otillar R, Salamov A, Schmutz J, Shapiro H, Lindquist E, Lucas S, Rokhsar D, Grigoriev IV (2011) The Selaginella genome identifies genetic changes associated with the evolution of vascular plants. Science 332: 960-963

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Genome Biol Evol%5BTitle%5D%29 AND 1%5BVolume%5D AND 391%5BPagination%5D AND Barker MS%2C Vogel H%2C Schranz ME%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Barker MS, Vogel H, Schranz ME (2009) Paleopolyploidy in the Brassicales: Analyses of the Cleome transcriptome elucidate the history of genome duplications in Arabidopsis and other Brassicales. Genome Biol Evol 1: 391-399

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http://scholar.google.com/scholar?as_q=Paleopolyploidy in the Brassicales: Analyses of the Cleome transcriptome elucidate the history of genome duplications in Arabidopsis and other Brassicales&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Paleopolyploidy in the Brassicales: Analyses of the Cleome transcriptome elucidate the history of genome duplications in Arabidopsis and other Brassicales&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Barker&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nature%5BTitle%5D%29 AND 422%5BVolume%5D AND 433%5BPagination%5D AND Bowers JE%2C Chapman BA%2C Rong J%2C Paterson AH%5BAuthor%5D&dopt=abstract

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Cenci A, Combes M-C, Lashermes P (2010) Comparative sequence analyses indicate that Coffea (Asterids) and Vitis (Rosids)derive from the same paleo-hexaploid ancestral genome. Mol Genet Genomics 283: 493-501


Chan AP, Crabtree J, Zhao Q, Lorenzi H, Orvis J, Puiu D, Melake-Berhan A, Jones KM, Redman J, Chen G, Cahoon EB, Gedil M,Stanke M, Haas BJ, Wortman JR, Fraser-Liggett CM, Ravel J, Rabinowicz PD (2010) Draft genome sequence of the oilseed speciesRicinus communis. Nat Biotechnol 28: 951-956


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Dassanayake M, Oh DH, Haas JS, Hernandez A, Hong H, Ali S, Yun DJ, Bressan RA, Zhu JK, Bohnert HJ, Cheeseman JM (2011)The genome of the extremophile crucifer Thellungiella parvula. Nat Genet 43: 913-918


De Mita S, Siol M (2012) EggLib: processing, analysis and simulation tools for population genetics and genomics. BMC Genet 13:27


De Smet I, Voss U, Jurgens G, Beeckman T (2009) Receptor-like kinases shape the plant. Nat Cell Biol 11: 1166-1173Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

De Smet R, Adams KL, Vandepoele K, Van Montagu MCE, Maere S, Van de Peer Y (2013) Convergent gene loss following geneand genome duplications creates single-copy families in flowering plants. Proc Natl Acad Sci USA 110: 2898-2903


Desper R, Gascuel O (2006) Getting a Tree Fast: Neighbor Joining, FastME, and Distance-Based Methods. In I John Wiley & Sons,ed, Curr Protoc Bioinformatics, pp 6.3.1-6.3.28


Dievart A, Gilbert N, Droc G, Attard A, Gourgues M, Guiderdoni E, Perin C (2011) Leucine-rich repeat receptor kinases aresporadically distributed in eukaryotic genomes. BMC Evol Biol 11: 367


Dodds PN, Rathjen JP (2010) Plant immunity: towards an integrated view of plant-pathogen interactions. Nat Rev Genet 11: 539-548Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Dou L, Zhang X, Pang C, Song M, Wei H, Fan S, Yu S (2014) Genome-wide analysis of the WRKY gene family in cotton. Mol GenetGenomics 289: 1103-1121



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http://scholar.google.com/scholar?as_q=Draft genome sequence of the oilseed species Ricinus communis&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Chan&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Proc Natl Acad Sci USA%5BTitle%5D%29 AND 102%5BVolume%5D AND 9074%5BPagination%5D AND Chevalier D%2C Batoux M%2C Fulton L%2C Pfister K%2C Yadav RK%2C Schellenberg M%2C Schneitz K%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Chevalier&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=STRUBBELIG defines a receptor kinase-mediated signaling pathway regulating organ development in Arabidopsis&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=STRUBBELIG defines a receptor kinase-mediated signaling pathway regulating organ development in Arabidopsis&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Chevalier&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nature%5BTitle%5D%29 AND 488%5BVolume%5D AND 213%5BPagination%5D AND D%27Hont A%2C Denoeud F%2C Aury JM%2C Baurens FC%2C Carreel F%2C Garsmeur O%2C Noel B%2C Bocs S%2C Droc G%2C Rouard M%2C Da Silva C%2C Jabbari K%2C Cardi C%2C Poulain J%2C Souquet M%2C Labadie K%2C Jourda C%2C Lengelle J%2C Rodier%2DGoud M%2C Alberti A%2C Bernard M%2C Correa M%2C Ayyampalayam S%2C McKain MR%2C Leebens%2DMack J%2C Burgess D%2C Freeling M%2C Mbeguie AMD%2C Chabannes M%2C Wicker T%2C Panaud O%2C Barbosa J%2C Hribova E%2C Heslop%2DHarrison P%2C Habas R%2C Rivallan R%2C Francois P%2C Poiron C%2C Kilian A%2C Burthia D%2C Jenny C%2C Bakry F%2C Brown S%2C Guignon V%2C Kema G%2C Dita M%2C Waalwijk C%2C Joseph S%2C Dievart A%2C Jaillon O%2C Leclercq J%2C Argout X%2C Lyons E%2C Almeida A%2C Jeridi M%2C Dolezel J%2C Roux N%2C Risterucci AM%2C Weissenbach J%2C Ruiz M%2C Glaszmann JC%2C Quetier F%2C Yahiaoui N%2C Wincker P%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Genet%5BTitle%5D%29 AND 43%5BVolume%5D AND 913%5BPagination%5D AND Dassanayake M%2C Oh DH%2C Haas JS%2C Hernandez A%2C Hong H%2C Ali S%2C Yun DJ%2C Bressan RA%2C Zhu JK%2C Bohnert HJ%2C Cheeseman JM%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28EggLib%3A processing%2C analysis and simulation tools for population genetics and genomics%2E%5BTitle%5D%29 AND De Mita S%2C Siol M%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Proc Natl Acad Sci USA%5BTitle%5D%29 AND 110%5BVolume%5D AND 2898%5BPagination%5D AND De Smet R%2C Adams KL%2C Vandepoele K%2C Van Montagu MCE%2C Maere S%2C Van de Peer Y%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Getting a Tree Fast%3A Neighbor Joining%2C FastME%2C and Distance%2DBased Methods%2E In I John Wiley %26 Sons%2C ed%2C Curr Protoc Bioinformatics%2C pp%5BTitle%5D%29 AND 6%5BVolume%5D AND 1%5BPagination%5D AND Desper R%2C Gascuel O%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Leucine-rich repeat receptor kinases are sporadically distributed in eukaryotic genomes.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Rev Genet%5BTitle%5D%29 AND 11%5BVolume%5D AND 539%5BPagination%5D AND Dodds PN%2C Rathjen JP%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Plant immunity: towards an integrated view of plant-pathogen interactions&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Dodds&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Mol Genet Genomics%5BTitle%5D%29 AND 289%5BVolume%5D AND 1103%5BPagination%5D AND Dou L%2C Zhang X%2C Pang C%2C Song M%2C Wei H%2C Fan S%2C Yu S%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Sequence analysis of the genome of an oil-bearing tree, Jatropha curcas L&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sato&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

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http://scholar.google.com/scholar?as_q=Genome structure of the legume, Lotus japonicus&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sato&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nature%5BTitle%5D%29 AND 463%5BVolume%5D AND 178%5BPagination%5D AND Schmutz J%2C Cannon SB%2C Schlueter J%2C Ma J%2C Mitros T%2C Nelson W%2C Hyten DL%2C Song Q%2C Thelen JJ%2C Cheng J%2C Xu D%2C Hellsten U%2C May GD%2C Yu Y%2C Sakurai T%2C Umezawa T%2C Bhattacharyya MK%2C Sandhu D%2C Valliyodan B%2C Lindquist E%2C Peto M%2C Grant D%2C Shu S%2C Goodstein D%2C Barry K%2C Futrell%2DGriggs M%2C Abernathy B%2C Du J%2C Tian Z%2C Zhu L%2C Gill N%2C Joshi T%2C Libault M%2C Sethuraman A%2C Zhang XC%2C Shinozaki K%2C Nguyen HT%2C Wing RA%2C Cregan P%2C Specht J%2C Grimwood J%2C Rokhsar D%2C Stacey G%2C Shoemaker RC%2C Jackson SA%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Differentiation of the maize subgenomes by genome dominance and both ancient and ongoing gene loss&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Schnable&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Science%5BTitle%5D%29 AND 326%5BVolume%5D AND 1112%5BPagination%5D AND Schnable PS%2C Ware D%2C Fulton RS%2C Stein JC%2C Wei F%2C Pasternak S%2C Liang C%2C Zhang J%2C Fulton L%2C Graves TA%2C Minx P%2C Reily AD%2C Courtney L%2C Kruchowski SS%2C Tomlinson C%2C Strong C%2C Delehaunty K%2C Fronick C%2C Courtney B%2C Rock SM%2C Belter E%2C Du F%2C Kim K%2C Abbott RM%2C Cotton M%2C Levy A%2C Marchetto P%2C Ochoa K%2C Jackson SM%2C Gillam B%2C Chen W%2C Yan L%2C Higginbotham J%2C Cardenas M%2C Waligorski J%2C Applebaum E%2C Phelps L%2C Falcone J%2C Kanchi K%2C Thane T%2C Scimone A%2C Thane N%2C Henke J%2C Wang T%2C Ruppert J%2C Shah N%2C Rotter K%2C Hodges J%2C Ingenthron E%2C Cordes M%2C Kohlberg S%2C Sgro J%2C Delgado B%2C Mead K%2C Chinwalla A%2C Leonard S%2C Crouse K%2C Collura K%2C Kudrna D%2C Currie J%2C He R%2C Angelova A%2C Rajasekar S%2C Mueller T%2C Lomeli R%2C Scara G%2C Ko A%2C Delaney K%2C Wissotski M%2C Lopez G%2C Campos D%2C Braidotti M%2C Ashley E%2C Golser W%2C Kim H%2C Lee S%2C Lin J%2C Dujmic Z%2C Kim W%2C Talag J%2C Zuccolo A%2C Fan C%2C Sebastian A%2C Kramer M%2C Spiegel L%2C Nascimento L%2C Zutavern T%2C Miller B%2C Ambroise C%2C Muller S%2C Spooner W%2C Narechania A%2C Ren L%2C Wei S%2C Kumari S%2C Faga B%2C Levy MJ%2C McMahan L%2C Van Buren P%2C Vaughn MW%2C Ying K%2C Yeh CT%2C Emrich SJ%2C Jia Y%2C Kalyanaraman A%2C Hsia AP%2C Barbazuk WB%2C Baucom RS%2C Brutnell TP%2C Carpita NC%2C Chaparro C%2C Chia JM%2C Deragon JM%2C Estill JC%2C Fu Y%2C Jeddeloh JA%2C Han Y%2C Lee H%2C Li P%2C Lisch DR%2C Liu S%2C Liu Z%2C Nagel DH%2C McCann MC%2C SanMiguel P%2C Myers AM%2C Nettleton D%2C Nguyen J%2C Penning BW%2C Ponnala L%2C Schneider KL%2C Schwartz DC%2C Sharma A%2C Soderlund C%2C Springer NM%2C Sun Q%2C Wang H%2C Waterman M%2C Westerman R%2C Wolfgruber TK%2C Yang L%2C Yu Y%2C Zhang L%2C Zhou S%2C Zhu Q%2C Bennetzen JL%2C Dawe RK%2C Jiang J%2C Jiang N%2C Presting GG%2C Wessler SR%2C Aluru S%2C Martienssen RA%2C Clifton SW%2C McCombie WR%2C Wing RA%2C Wilson RK%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=The B73 maize genome: complexity, diversity, and dynamics&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Schnable&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Chromosomal location%2C structure%2C phylogeny%2C and expression patterns%2E J Integr Plant Biol%5BTitle%5D%29 AND 55%5BVolume%5D AND 663%5BPagination%5D AND Shang H%2C Li W%2C Zou C%2C Yuan Y%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Analyses of the NAC transcription factor gene family in Gossypium raimondii Ulbr&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Analyses of the NAC transcription factor gene family in Gossypium raimondii Ulbr&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Shang&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Sci%2E STKE%5BTitle%5D%29 AND 2001%5BVolume%5D AND re22%5BPagination%5D AND Shiu S%2DH%2C Bleecker AB%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Comparative analysis of the Receptor-Like Kinase family in Arabidopsis and rice&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Shiu&as_ylo=2004&as_allsubj=all&hl=en&c2coff=1


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Soltis DE, Burleigh JG (2009) Surviving the K-T mass extinction: New perspectives of polyploidization in angiosperms. Proc NatlAcad Sci USA 106: 5455-5456


Song X, Guo P, Li C, Liu C-M (2010) The cysteine pairs in CLV2 are not necessary for sensing the CLV3 peptide in shoot and rootmeristems. J Integr Plant Biol 52: 774-781


Sun W, Cao Y, Jansen Labby K, Bittel P, Boller T, Bent AF (2012) Probing the Arabidopsis Flagellin Receptor: FLS2-FLS2association and the contributions of specific domains to signaling function. Plant Cell 24: 1096-1113


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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Am J Bot%5BTitle%5D%29 AND 96%5BVolume%5D AND 336%5BPagination%5D AND Soltis DE%2C Albert VA%2C Leebens%2DMack J%2C Bell CD%2C Paterson AH%2C Zheng C%2C Sankoff D%2C dePamphilis CW%2C Wall PK%2C Soltis PS%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Soltis DE, Albert VA, Leebens-Mack J, Bell CD, Paterson AH, Zheng C, Sankoff D, dePamphilis CW, Wall PK, Soltis PS (2009) Polyploidy and angiosperm diversification. Am J Bot 96: 336-348

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Soltis&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Polyploidy and angiosperm diversification&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Polyploidy and angiosperm diversification&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Soltis&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Proc Natl Acad Sci USA%5BTitle%5D%29 AND 106%5BVolume%5D AND 5455%5BPagination%5D AND Soltis DE%2C Burleigh JG%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Soltis&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Surviving the K-T mass extinction: New perspectives of polyploidization in angiosperms&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Surviving the K-T mass extinction: New perspectives of polyploidization in angiosperms&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Soltis&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28J Integr Plant Biol%5BTitle%5D%29 AND 52%5BVolume%5D AND 774%5BPagination%5D AND Song X%2C Guo P%2C Li C%2C Liu C%2DM%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Song X, Guo P, Li C, Liu C-M (2010) The cysteine pairs in CLV2 are not necessary for sensing the CLV3 peptide in shoot and root meristems. J Integr Plant Biol 52: 774-781

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Song&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=The cysteine pairs in CLV2 are not necessary for sensing the CLV3 peptide in shoot and root meristems&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=The cysteine pairs in CLV2 are not necessary for sensing the CLV3 peptide in shoot and root meristems&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Song&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Plant Cell%5BTitle%5D%29 AND 24%5BVolume%5D AND 1096%5BPagination%5D AND Sun W%2C Cao Y%2C Jansen Labby K%2C Bittel P%2C Boller T%2C Bent AF%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Sun W, Cao Y, Jansen Labby K, Bittel P, Boller T, Bent AF (2012) Probing the Arabidopsis Flagellin Receptor: FLS2-FLS2 association and the contributions of specific domains to signaling function. Plant Cell 24: 1096-1113

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Sun&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Probing the Arabidopsis Flagellin Receptor: FLS2-FLS2 association and the contributions of specific domains to signaling function&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Probing the Arabidopsis Flagellin Receptor: FLS2-FLS2 association and the contributions of specific domains to signaling function&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sun&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Genetica%5BTitle%5D%29 AND 139%5BVolume%5D AND 1465%5BPagination%5D AND Tan S%2C Wang D%2C Ding J%2C Tian D%2C Zhang X%2C Yang S%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Tan S, Wang D, Ding J, Tian D, Zhang X, Yang S (2011) Adaptive evolution of Xa21 homologs in Gramineae. Genetica 139: 1465-1475

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Tan&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Adaptive evolution of Xa21 homologs in Gramineae&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Adaptive evolution of Xa21 homologs in Gramineae&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tan&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Proc Natl Acad Sci USA%5BTitle%5D%29 AND 107%5BVolume%5D AND 472%5BPagination%5D AND Tang H%2C Bowers JE%2C Wang X%2C Paterson AH%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Tang H, Bowers JE, Wang X, Paterson AH (2010a) Angiosperm genome comparisons reveal early polyploidy in the monocot lineage. Proc Natl Acad Sci USA 107: 472-477

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Tang&hl=en&c2coff=1

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http://scholar.google.com/scholar?as_q=The genome of the domesticated apple (Malus x domestica Borkh&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=The genome of the domesticated apple (Malus x domestica Borkh&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Velasco&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Genet%5BTitle%5D%29 AND 45%5BVolume%5D AND 487%5BPagination%5D AND Verde I%2C Abbott AG%2C Scalabrin S%2C Jung S%2C Shu S%2C Marroni F%2C Zhebentyayeva T%2C Dettori MT%2C Grimwood J%2C Cattonaro F%2C Zuccolo A%2C Rossini L%2C Jenkins J%2C Vendramin E%2C Meisel LA%2C Decroocq V%2C Sosinski B%2C Prochnik S%2C Mitros T%2C Policriti A%2C Cipriani G%2C Dondini L%2C Ficklin S%2C Goodstein DM%2C Xuan P%2C Fabbro CD%2C Aramini V%2C Copetti D%2C Gonzalez S%2C Horner DS%2C Falchi R%2C Lucas S%2C Mica E%2C Maldonado J%2C Lazzari B%2C Bielenberg D%2C Pirona R%2C Miculan M%2C Barakat A%2C Testolin R%2C Stella A%2C Tartarini S%2C Tonutti P%2C Arus P%2C Orellana A%2C Wells C%2C Main D%2C Vizzotto G%2C Silva H%2C Salamini F%2C Schmutz J%2C Morgante M%2C Rokhsar DS%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=The high-quality draft genome of peach (Prunus persica) identifies unique patterns of genetic diversity, domestication and genome evolution&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Verde&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Mol Biol Evol%5BTitle%5D%29 AND 29%5BVolume%5D AND 1655%5BPagination%5D AND Vetter MM%2C Kronholm I%2C He F%2C Haweker H%2C Reymond M%2C Bergelson J%2C Robatzek S%2C de Meaux J%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Flagellin perception varies quantitatively in Arabidopsis thaliana and its relatives&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Vetter&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Plant Cell%5BTitle%5D%29 AND 10%5BVolume%5D AND 765%5BPagination%5D AND Wang G%2DL%2C Ruan D%2DL%2C Song W%2DY%2C Sideris S%2C Chen L%2C Pi L%2DY%2C Zhang S%2C Zhang Z%2C Fauquet C%2C Gaut BS%2C Whalen MC%2C Ronald PC%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Wang G-L, Ruan D-L, Song W-Y, Sideris S, Chen L, Pi L-Y, Zhang S, Zhang Z, Fauquet C, Gaut BS, Whalen MC, Ronald PC (1998) Xa21D encodes a receptor-like molecule with a Leucine-Rich Repeat domain that determines race-specific recognition and is subject to adaptive evolution. Plant Cell 10: 765-779

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Wang&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Xa21D encodes a receptor-like molecule with a Leucine-Rich Repeat domain that determines race-specific recognition and is subject to adaptive evolution&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Xa21D encodes a receptor-like molecule with a Leucine-Rich Repeat domain that determines race-specific recognition and is subject to adaptive evolution&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=1998&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Genet%5BTitle%5D%29 AND 44%5BVolume%5D AND 1098%5BPagination%5D AND Wang K%2C Wang Z%2C Li F%2C Ye W%2C Wang J%2C Song G%2C Yue Z%2C Cong L%2C Shang H%2C Zhu S%2C Zou C%2C Li Q%2C Yuan Y%2C Lu C%2C Wei H%2C Gou C%2C Zheng Z%2C Yin Y%2C Zhang X%2C Liu K%2C Wang B%2C Song C%2C Shi N%2C Kohel RJ%2C Percy RG%2C Yu JZ%2C Zhu YX%2C Wang J%2C Yu S%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Wang K, Wang Z, Li F, Ye W, Wang J, Song G, Yue Z, Cong L, Shang H, Zhu S, Zou C, Li Q, Yuan Y, Lu C, Wei H, Gou C, Zheng Z, Yin Y, Zhang X, Liu K, Wang B, Song C, Shi N, Kohel RJ, Percy RG, Yu JZ, Zhu YX, Wang J, Yu S (2012) The draft genome of a diploid cotton Gossypium raimondii. Nat Genet 44: 1098-1103


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http://scholar.google.com/scholar?as_q=The draft genome of a diploid cotton Gossypium raimondii&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Genet%5BTitle%5D%29 AND 43%5BVolume%5D AND 1035%5BPagination%5D AND Wang X%2C Wang H%2C Wang J%2C Sun R%2C Wu J%2C Liu S%2C Bai Y%2C Mun JH%2C Bancroft I%2C Cheng F%2C Huang S%2C Li X%2C Hua W%2C Wang J%2C Wang X%2C Freeling M%2C Pires JC%2C Paterson AH%2C Chalhoub B%2C Wang B%2C Hayward A%2C Sharpe AG%2C Park BS%2C Weisshaar B%2C Liu B%2C Li B%2C Liu B%2C Tong C%2C Song C%2C Duran C%2C Peng C%2C Geng C%2C Koh C%2C Lin C%2C Edwards D%2C Mu D%2C Shen D%2C Soumpourou E%2C Li F%2C Fraser F%2C Conant G%2C Lassalle G%2C King GJ%2C Bonnema G%2C Tang H%2C Wang H%2C Belcram H%2C Zhou H%2C Hirakawa H%2C Abe H%2C Guo H%2C Wang H%2C Jin H%2C Parkin IA%2C Batley J%2C Kim JS%2C Just J%2C Li J%2C Xu J%2C Deng J%2C Kim JA%2C Li J%2C Yu J%2C Meng J%2C Wang J%2C Min J%2C Poulain J%2C Wang J%2C Hatakeyama K%2C Wu K%2C Wang L%2C Fang L%2C Trick M%2C Links MG%2C Zhao M%2C Jin M%2C Ramchiary N%2C Drou N%2C Berkman PJ%2C Cai Q%2C Huang Q%2C Li R%2C Tabata S%2C Cheng S%2C Zhang S%2C Zhang S%2C Huang S%2C Sato S%2C Sun S%2C Kwon SJ%2C Choi SR%2C Lee TH%2C Fan W%2C Zhao X%2C Tan X%2C Xu X%2C Wang Y%2C Qiu Y%2C Yin Y%2C Li Y%2C Du Y%2C Liao Y%2C Lim Y%2C Narusaka Y%2C Wang Y%2C Wang Z%2C Li Z%2C Wang Z%2C Xiong Z%2C Zhang Z%2C Brassica rapa Genome Sequencing Project C%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Wang X, Wang H, Wang J, Sun R, Wu J, Liu S, Bai Y, Mun JH, Bancroft I, Cheng F, Huang S, Li X, Hua W, Wang J, Wang X, Freeling M, Pires JC, Paterson AH, Chalhoub B, Wang B, Hayward A, Sharpe AG, Park BS, Weisshaar B, Liu B, Li B, Liu B, Tong C, Song C, Duran C, Peng C, Geng C, Koh C, Lin C, Edwards D, Mu D, Shen D, Soumpourou E, Li F, Fraser F, Conant G, Lassalle G, King GJ, Bonnema G, Tang H, Wang H, Belcram H, Zhou H, Hirakawa H, Abe H, Guo H, Wang H, Jin H, Parkin IA, Batley J, Kim JS, Just J, Li J, Xu J, Deng J, Kim JA, Li J, Yu J, Meng J, Wang J, Min J, Poulain J, Wang J, Hatakeyama K, Wu K, Wang L, Fang L, Trick M, Links MG, Zhao M, Jin M, Ramchiary N, Drou N, Berkman PJ, Cai Q, Huang Q, Li R, Tabata S, Cheng S, Zhang S, Zhang S, Huang S, Sato S, Sun S, Kwon SJ, Choi SR, Lee TH, Fan W, Zhao X, Tan X, Xu X, Wang Y, Qiu Y, Yin Y, Li Y, Du Y, Liao Y, Lim Y, Narusaka Y, Wang Y, Wang Z, Li Z, Wang Z, Xiong Z, Zhang Z, Brassica rapa Genome Sequencing Project C (2011) The genome of the mesopolyploid crop species Brassica rapa. Nat Genet 43: 1035-1039


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http://scholar.google.com/scholar?as_q=The genome of the mesopolyploid crop species Brassica rapa&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Proc Natl Acad Sci USA%5BTitle%5D%29 AND 109%5BVolume%5D AND 12219%5BPagination%5D AND Wu H%2DJ%2C Zhang Z%2C Wang J%2DY%2C Oh D%2DH%2C Dassanayake M%2C Liu B%2C Huang Q%2C Sun H%2DX%2C Xia R%2C Wu Y%2C Wang Y%2DN%2C Yang Z%2C Liu Y%2C Zhang W%2C Zhang H%2C Chu J%2C Yan C%2C Fang S%2C Zhang J%2C Wang Y%2C Zhang F%2C Wang G%2C Lee SY%2C Cheeseman JM%2C Yang B%2C Li B%2C Min J%2C Yang L%2C Wang J%2C Chu C%2C Chen S%2DY%2C Bohnert HJ%2C Zhu J%2DK%2C Wang X%2DJ%2C Xie Q%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Wu H-J, Zhang Z, Wang J-Y, Oh D-H, Dassanayake M, Liu B, Huang Q, Sun H-X, Xia R, Wu Y, Wang Y-N, Yang Z, Liu Y, Zhang W, Zhang H, Chu J, Yan C, Fang S, Zhang J, Wang Y, Zhang F, Wang G, Lee SY, Cheeseman JM, Yang B, Li B, Min J, Yang L, Wang J, Chu C, Chen S-Y, Bohnert HJ, Zhu J-K, Wang X-J, Xie Q (2012) Insights into salt tolerance from the genome of Thellungiella salsuginea. Proc Natl Acad Sci USA 109: 12219-12224

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Wu&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Insights into salt tolerance from the genome of Thellungiella salsuginea&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Insights into salt tolerance from the genome of Thellungiella salsuginea&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wu&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28New Phytol%5BTitle%5D%29 AND 193%5BVolume%5D AND 1022%5BPagination%5D AND Xue Z%2C Duan L%2C Liu D%2C Guo J%2C Ge S%2C Dicks J%2C �M�ille P%2C Osbourn A%2C Qi X%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Xue&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Divergent evolution of oxidosqualene cyclases in plants&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Divergent evolution of oxidosqualene cyclases in plants&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Xue&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28J Biol Chem%5BTitle%5D%29 AND 285%5BVolume%5D AND 7119%5BPagination%5D AND Yang T%2C Chaudhuri S%2C Yang L%2C Du L%2C Poovaiah BW%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Yang T, Chaudhuri S, Yang L, Du L, Poovaiah BW (2010) A calcium/calmodulin-regulated member of the Receptor-like Kinase family confers cold tolerance in plants. J Biol Chem 285: 7119-7126

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http://scholar.google.com/scholar?as_q=A calcium/calmodulin-regulated member of the Receptor-like Kinase family confers cold tolerance in plants&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=A calcium/calmodulin-regulated member of the Receptor-like Kinase family confers cold tolerance in plants&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Yang&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1


Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24: 1586-1591Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Yang Z, Wang Y, Zhou Y, Gao Q, Zhang E, Zhu L, Hu Y, Xu C (2013a) Evolution of land plant genes encoding L-Ala-D/L-Gluepimerases (AEEs) via horizontal gene transfer and positive selection. BMC Plant Biol 13: 34


Yang ZL, Liu HJ, Wang XR, Zeng QY (2013b) Molecular evolution and expression divergence of the Populus polygalacturonasesupergene family shed light on the evolution of increasingly complex organs in plants. New Phytol 197: 1353-1365


Young ND, Debelle F, Oldroyd GE, Geurts R, Cannon SB, Udvardi MK, Benedito VA, Mayer KF, Gouzy J, Schoof H, Van de Peer Y,Proost S, Cook DR, Meyers BC, Spannagl M, Cheung F, De Mita S, Krishnakumar V, Gundlach H, Zhou S, Mudge J, Bharti AK,Murray JD, Naoumkina MA, Rosen B, Silverstein KA, Tang H, Rombauts S, Zhao PX, Zhou P, Barbe V, Bardou P, Bechner M, BellecA, Berger A, Berges H, Bidwell S, Bisseling T, Choisne N, Couloux A, Denny R, Deshpande S, Dai X, Doyle JJ, Dudez AM, FarmerAD, Fouteau S, Franken C, Gibelin C, Gish J, Goldstein S, Gonzalez AJ, Green PJ, Hallab A, Hartog M, Hua A, Humphray SJ, JeongDH, Jing Y, Jocker A, Kenton SM, Kim DJ, Klee K, Lai H, Lang C, Lin S, Macmil SL, Magdelenat G, Matthews L, McCorrison J,Monaghan EL, Mun JH, Najar FZ, Nicholson C, Noirot C, O'Bleness M, Paule CR, Poulain J, Prion F, Qin B, Qu C, Retzel EF, RiddleC, Sallet E, Samain S, Samson N, Sanders I, Saurat O, Scarpelli C, Schiex T, Segurens B, Severin AJ, Sherrier DJ, Shi R, Sims S,Singer SR, Sinharoy S, Sterck L, Viollet A, Wang BB, Wang K, Wang M, Wang X, Warfsmann J, Weissenbach J, White DD, White JD,Wiley GB, Wincker P, Xing Y, Yang L, Yao Z, Ying F, Zhai J, Zhou L, Zuber A, Denarie J, Dixon RA, May GD, Schwartz DC, Rogers J,Quetier F, Town CD, Roe BA (2011) The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature 480:520-524


Yu J, Hu S, Wang J, Wong GK-S, Li S, Liu B, Deng Y, Dai L, Zhou Y, Zhang X, Cao M, Liu J, Sun J, Tang J, Chen Y, Huang X, Lin W,Ye C, Tong W, Cong L, Geng J, Han Y, Li L, Li W, Hu G, Huang X, Li W, Li J, Liu Z, Li L, Liu J, Qi Q, Liu J, Li L, Li T, Wang X, Lu H,Wu T, Zhu M, Ni P, Han H, Dong W, Ren X, Feng X, Cui P, Li X, Wang H, Xu X, Zhai W, Xu Z, Zhang J, He S, Zhang J, Xu J, Zhang K,Zheng X, Dong J, Zeng W, Tao L, Ye J, Tan J, Ren X, Chen X, He J, Liu D, Tian W, Tian C, Xia H, Bao Q, Li G, Gao H, Cao T, Wang J,Zhao W, Li P, Chen W, Wang X, Zhang Y, Hu J, Wang J, Liu S, Yang J, Zhang G, Xiong Y, Li Z, Mao L, Zhou C, Zhu Z, Chen R, Hao B,Zheng W, Chen S, Guo W, Li G, Liu S, Tao M, Wang J, Zhu L, Yuan L, Yang H (2002) A draft sequence of the rice genome (Oryzasativa L. ssp. indica). Science 296: 79-92


Zhang G, Liu X, Quan Z, Cheng S, Xu X, Pan S, Xie M, Zeng P, Yue Z, Wang W, Tao Y, Bian C, Han C, Xia Q, Peng X, Cao R, Yang X,Zhan D, Hu J, Zhang Y, Li H, Li H, Li N, Wang J, Wang C, Wang R, Guo T, Cai Y, Liu C, Xiang H, Shi Q, Huang P, Chen Q, Li Y, WangJ, Zhao Z, Wang J (2012) Genome sequence of foxtail millet (Setaria italica) provides insights into grass evolution and biofuelpotential. Nat Biotechnol 30: 549-554


Zhang X, Choi J, Heinz J, Chetty C (2006) Domain-specific positive selection contributes to the evolution of Arabidopsis Leucine-Rich Repeat Receptor-Like Kinase (LRR RLK) genes. J Mol Evol 63: 612-621


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http://www.ncbi.nlm.nih.gov/pubmed?term=%28PAML%5BTitle%5D%29 AND 4%5BVolume%5D AND phylogenetic analysis by maximum likelihood%2E Mol Biol Evol 24%3A 1586%5BPagination%5D AND Yang Z%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24: 1586-1591



http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Yang&as_ylo=2007&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Evolution of land plant genes encoding L%2DAla%2DD%2FL%2DGlu epimerases AEEs via horizontal gene transfer and positive selection%2E%5BTitle%5D%29 AND Yang Z%2C Wang Y%2C Zhou Y%2C Gao Q%2C Zhang E%2C Zhu L%2C Hu Y%2C Xu C%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Yang Z, Wang Y, Zhou Y, Gao Q, Zhang E, Zhu L, Hu Y, Xu C (2013a) Evolution of land plant genes encoding L-Ala-D/L-Glu epimerases (AEEs) via horizontal gene transfer and positive selection. BMC Plant Biol 13: 34


http://scholar.google.com/scholar?as_q=Evolution of land plant genes encoding L-Ala-D/L-Glu epimerases (AEEs) via horizontal gene transfer and positive selection.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Evolution of land plant genes encoding L-Ala-D/L-Glu epimerases (AEEs) via horizontal gene transfer and positive selection.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Yang&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28New Phytol%5BTitle%5D%29 AND 197%5BVolume%5D AND 1353%5BPagination%5D AND Yang ZL%2C Liu HJ%2C Wang XR%2C Zeng QY%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Yang ZL, Liu HJ, Wang XR, Zeng QY (2013b) Molecular evolution and expression divergence of the Populus polygalacturonase supergene family shed light on the evolution of increasingly complex organs in plants. New Phytol 197: 1353-1365


http://scholar.google.com/scholar?as_q=Molecular evolution and expression divergence of the Populus polygalacturonase supergene family shed light on the evolution of increasingly complex organs in plants&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Molecular evolution and expression divergence of the Populus polygalacturonase supergene family shed light on the evolution of increasingly complex organs in plants&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Yang&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nature%5BTitle%5D%29 AND 480%5BVolume%5D AND 520%5BPagination%5D AND Young ND%2C Debelle F%2C Oldroyd GE%2C Geurts R%2C Cannon SB%2C Udvardi MK%2C Benedito VA%2C Mayer KF%2C Gouzy J%2C Schoof H%2C Van de Peer Y%2C Proost S%2C Cook DR%2C Meyers BC%2C Spannagl M%2C Cheung F%2C De Mita S%2C Krishnakumar V%2C Gundlach H%2C Zhou S%2C Mudge J%2C Bharti AK%2C Murray JD%2C Naoumkina MA%2C Rosen B%2C Silverstein KA%2C Tang H%2C Rombauts S%2C Zhao PX%2C Zhou P%2C Barbe V%2C Bardou P%2C Bechner M%2C Bellec A%2C Berger A%2C Berges H%2C Bidwell S%2C Bisseling T%2C Choisne N%2C Couloux A%2C Denny R%2C Deshpande S%2C Dai X%2C Doyle JJ%2C Dudez AM%2C Farmer AD%2C Fouteau S%2C Franken C%2C Gibelin C%2C Gish J%2C Goldstein S%2C Gonzalez AJ%2C Green PJ%2C Hallab A%2C Hartog M%2C Hua A%2C Humphray SJ%2C Jeong DH%2C Jing Y%2C Jocker A%2C Kenton SM%2C Kim DJ%2C Klee K%2C Lai H%2C Lang C%2C Lin S%2C Macmil SL%2C Magdelenat G%2C Matthews L%2C McCorrison J%2C Monaghan EL%2C Mun JH%2C Najar FZ%2C Nicholson C%2C Noirot C%2C O%27Bleness M%2C Paule CR%2C Poulain J%2C Prion F%2C Qin B%2C Qu C%2C Retzel EF%2C Riddle C%2C Sallet E%2C Samain S%2C Samson N%2C Sanders I%2C Saurat O%2C Scarpelli C%2C Schiex T%2C Segurens B%2C Severin AJ%2C Sherrier DJ%2C Shi R%2C Sims S%2C Singer SR%2C Sinharoy S%2C Sterck L%2C Viollet A%2C Wang BB%2C Wang K%2C Wang M%2C Wang X%2C Warfsmann J%2C Weissenbach J%2C White DD%2C White JD%2C Wiley GB%2C Wincker P%2C Xing Y%2C Yang L%2C Yao Z%2C Ying F%2C Zhai J%2C Zhou L%2C Zuber A%2C Denarie J%2C Dixon RA%2C May GD%2C Schwartz DC%2C Rogers J%2C Quetier F%2C Town CD%2C Roe BA%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Young ND, Debelle F, Oldroyd GE, Geurts R, Cannon SB, Udvardi MK, Benedito VA, Mayer KF, Gouzy J, Schoof H, Van de Peer Y, Proost S, Cook DR, Meyers BC, Spannagl M, Cheung F, De Mita S, Krishnakumar V, Gundlach H, Zhou S, Mudge J, Bharti AK, Murray JD, Naoumkina MA, Rosen B, Silverstein KA, Tang H, Rombauts S, Zhao PX, Zhou P, Barbe V, Bardou P, Bechner M, Bellec A, Berger A, Berges H, Bidwell S, Bisseling T, Choisne N, Couloux A, Denny R, Deshpande S, Dai X, Doyle JJ, Dudez AM, Farmer AD, Fouteau S, Franken C, Gibelin C, Gish J, Goldstein S, Gonzalez AJ, Green PJ, Hallab A, Hartog M, Hua A, Humphray SJ, Jeong DH, Jing Y, Jocker A, Kenton SM, Kim DJ, Klee K, Lai H, Lang C, Lin S, Macmil SL, Magdelenat G, Matthews L, McCorrison J, Monaghan EL, Mun JH, Najar FZ, Nicholson C, Noirot C, O'Bleness M, Paule CR, Poulain J, Prion F, Qin B, Qu C, Retzel EF, Riddle C, Sallet E, Samain S, Samson N, Sanders I, Saurat O, Scarpelli C, Schiex T, Segurens B, Severin AJ, Sherrier DJ, Shi R, Sims S, Singer SR, Sinharoy S, Sterck L, Viollet A, Wang BB, Wang K, Wang M, Wang X, Warfsmann J, Weissenbach J, White DD, White JD, Wiley GB, Wincker P, Xing Y, Yang L, Yao Z, Ying F, Zhai J, Zhou L, Zuber A, Denarie J, Dixon RA, May GD, Schwartz DC, Rogers J, Quetier F, Town CD, Roe BA (2011) The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature 480: 520-524

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Young&hl=en&c2coff=1

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4 Corresponding Authors: 5 Iris Fischer (irisfischer402 ... Iris Fischer ([email protected]) and Nathalie Chantret ([email protected]) 6 INRA SupAgro, UMR AGAP, 2 Place