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bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

1 Evidence for two main trajectories in 2 cerevisiae linked to distinct -making processes

3 Frédéric Bigey1, Diego Segond1, Anne Friedrich4, Stephane Guezenec1, Aurélie Bourgais2, 4 Lucie Huyghe2‡, Nicolas Agier3, Thibault Nidelet1, Delphine Sicard1*

5 1 SPO, INRAE, Univ. Montpellier, Montpellier SupAgro, Montpellier, France; 6 2 GQE-Le Moulon, INRAE, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris- 7 Saclay, Gif-sur-Yvette, France; 8 3 Sorbonne Université, CNRS, Institut de Biologie Paris-Seine, Laboratory of 9 Computational and Quantitative Biology, F-75005 Paris, France; 10 4 Université de Strasbourg, CNRS, GMGM UMR 7156, F-67000 Strasbourg, France

11 ‡ Present address: McGill University, Canada

12 * For correspondence: delphine.sicard@inra e .fr

13 Keywords

14 , tetraploid, Saccharomyces, , bread bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

15 Summary

16 Despite bread being one of the most historically and culturally important fermented 17 products, its history and influence on the of associated microbial species remains 18 largely unknown. The first evidence of leavened bread dates to the second millenium BCE 19 in Egypt and since, the art of bread-making developed and spread worldwide. Nowadays, 20 leavened bread is made either by using a pure commercial culture of the yeast 21 Saccharomyces cerevisiae or by propagating a sourdough, which is a mix of and 22 spontaneously fermented by yeast and . We studied the domestication of 23 S. cerevisiae populations originating from industry and sourdough and tested whether these 24 different bread-making processes led to population divergence. We found that the origin of 25 S. cerevisiae bakery strains is polyphyletic with 67 % of strains clustering in two main 26 clades: most commercial strains were tetraploid and clustered with strains having diverse 27 origins, including . By contrast, most sourdough strains were diploids and found in a 28 second clade of strains having and diverse origins including fruits, or 29 clinical and wild environments. When compared to the others, sourdough strains harboured 30 in average a higher copy number of involved in utilization, a common 31 produced from dough starch. Overall, a high level of flow from multiple contributors 32 was detected. Phenotyping of bakery and non bakery strains further showed that sourdough 33 and industrial bakery populations have undergone human selection for rapidly starting

34 and for high CO2 production. Interestingly, sourdough strains also showed a 35 better adaptation to a sourdough mimicking environment, suggesting that natural selection 36 occurred as well. In summary, our results revealed that the domestication of bakery yeast 37 populations has been accompanied by dispersion, hybridization and divergent selection 38 through industrial and artisanal bakery processes. In addition, they unveiled for the first time 39 a case of domestication where species divergence occurred through 40 autotetraploidisation. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

41 Introduction

42 The domestication of microbes is an ancient process that has accompanied fermented food 43 processing since at least Neolithic times, when plant and animal domestication first occurred 44 [1–7]. Until recently, the evolutionary history of domesticated microbes was poorly 45 documented[2,3]. Most studies focused on the filamentous fungi Aspergillus oryzae used in 46 rice and soya and Penicillium roqueforti used for making blue cheese [8–10] 47 as well as on the Saccharomyces cerevisiae yeast model species. This last species is found in 48 many natural habitats (soil, tree bark, water… ) and has been domesticated for the 49 production of a large diversity of fermented drinks (wine, beer, sake, cachaça, coffee, 50 fermented ) and foods (bread, cocoa, olives) [4,11]. Wild populations isolated from 51 natural habitats present a broader and distinct genetic diversity than populations isolated 52 from anthropogenic environments, suggesting that the latter were selected from the wild by 53 humans for food processing [12,13]. The China/far East Asia area may likely be one center 54 of origin of the domesticated populations [14]. 55 The domestication of S. cerevisiae has been well described for wine, beer, sake, cachaça, 56 cocoa, and coffee but surprisingly not for bread [14–16]. Domestication for making different 57 products has led to a genetic diversification of strains that group together according to the 58 fermentation type, but it also led to phenotypic divergence. Indeed, parallel domestication 59 processes occurred for different beverages and foods although some gene flow between 60 domesticated strains have been detected [12]. Wine strains and the closely related group of 61 flor strains likely have a single origin [17–20]. Sake strains also appear to have evolved from 62 a single origin [12,15,21] while cachaça strains evolved from wine strains through a 63 secondary domestication process [22]. Coffee, cocoa and beer strains have a more complex 64 evolutionary history where both migration and selection played major roles [23–27]. Several 65 genetic signatures associated with human selection have been detected in all these 66 domesticated populations, including SNPs [19,23,27], gene duplication [23,28,29], 67 [17–19,30], and hybridization [21]. Despite the cultural and 68 historical importance of bread, the study of bakery strains domestication has been neglected. 69 This might be related to the fact that several industrial bakery yeast starters have been found 70 to be autotetraploid [31], which renders population genomic analysis complicated [32,33]. 71 The earliest evidence of leavened bread was found during antiquity in the second millennium 72 BCE in Egypt [34] and in the first millenium BCE in North West China [35]. Since then, the 73 art of making leavened bread developed during ancient and medieval ages and was 74 disseminated throughout the Mediterranean and in Middle East countries (Carbonetto et al. 75 2018). At that time, bread making consisted in mixing flour, water, and sourdough, a mix of bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 76 flour and water containing fermenting microbes. In the 19th century, the industrialization of 77 food production and the advent of microbiology as a science resulted in the production of 78 pure yeast cultures that were used as starter to make bread. The production of bread made 79 with commercial S. cerevisiae yeast starter soon spread all over the world. Yet, nowadays, 80 global changes and the increase in the of non-communicable diseases related to 81 modern diets (including type 2 diabetes, obesity, food allergies) have led to a renewed 82 interest in traditional methods of bread making and in its local production. The appeal of 83 traditionally prepared is underpinned by research showing improved flavour and 84 nutritional benefits in sourdough bread made by artisanal bakers [36–38]. Therefore, both 85 ways of making leavened bread are currently found and bakers either use commercial , 86 or natural . 87 Natural sourdough is made from flour and water and maintained by recurrent addition of 88 flour and water, a process called backslopping. Sourdough contains a microbial community 89 consisting of lactic acid bacteria and yeasts with a ratio of 100:1 on average [39]. One or two 90 prevailing species of lactic acid bacteria and one prevailing yeast species are usually found. 91 The yeast species found in sourdough mainly belong to the genera Saccharomyces sensus 92 stricto, Kazachstania, Pichia, Torulaspora. Worldwide, S. cerevisiae is the most widespread 93 species found in sourdoughs [40] made by bakers, but also in sourdough made by farmers- 94 bakers [41,42]. It can be found as the dominant species in sourdough, even in bakeries 95 where no industrial starter is used, suggesting that the species may colonize a sourdough 96 from the bakery’s environment or the baker’s hands [43]. Therefore, bakery strains of S. 97 cerevisiae may have undergone different domestication processes. While industrial bread 98 production may have led to the breeding and selection of homogeneous lineages of yeast 99 starters, artisanal bread making may have selected strains through the continuous, long-term 100 maintenance of sourdough microbial communities. These two types of domestication 101 processes also apply to many different fermented foods. [2]. Until recently however, study of 102 fungi domestication mostly revealed footprints of industrial selection [9]. The renewed 103 interest in traditional sourdough bread production makes the S. cerevisiae bakery 104 populations an excellent model for the study of the impact of both artisanal and industrial 105 practices on fungi evolution and adaptation. 106 The objective of this study was to investigate the evolutionary history of S. cerevisiae 107 isolated in bakeries. We examined whether bakery strains had either a single or several 108 genetic origins and studied the genetic diversity and genetic relationship of commercial and 109 natural sourdough strains. In addition, we studied to what extent gene and genome 110 duplication have been involved in the domestication of S. cerevisiae in bakeries. We found 111 that bakery strains are polyphyletic and found in clades that also contain strains from other 112 domesticated environments, suggesting no specific origin for bakery strains. Except for a 113 few strains that clustered with wine or African beer fermentation strains, bakery strains were bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 114 mostly grouped in two main clades, each composed of two subgroups. One mostly grouped 115 commercial strains while the other mostly contained sourdough strains, suggesting different 116 domestication roads for commercial and sourdough strains. Commercial strains appeared to 117 be most often tetraploid and to display a shorter fermentation latency phase while sourdough 118 strains appeared to have most often duplication of Maltose and Isomaltose maltase and 119 permease genes, revealing different genetic and phenotypic signatures for industrial and 120 artisanal selection. A overall high proportion of admixture was detected and some 121 sourdough strains clustered together with commercial strains, suggesting that gene flow is 122 also an important process in the evolution of bakery strains. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

123 Results

124 Prevalent tetraploidy and aneuploidy in commercial bakery strains

125 Polyploidization, which refers to the multiplication of a complete chromosome set, has been 126 found to be associated with domestication in plants, but also in Saccharomyces cerevisiae 127 beer strains [23,44]. A previous analysis of 26 S. cerevisiae strains originating from diverse 128 fermented products showed that most bakery strains analyzed were autotetraploid, 129 suggesting that bakery yeast domestication was also associated with polyploidization [31]. 130 We therefore analysed the of a set of 229 bakery S. cerevisiae strains (Table S1) 131 using a combination of microsatellite typing and flow cytometry analysis. Thirty-one strains 132 were commercial yeasts and 198 were isolated from European sourdoughs collected in Italy, 133 Belgium and France. An overall high level of tetraploidy (40%) and aneuploidy (17%) was 134 observed (Table 1). We found that commercial strains were significantly (two sided Fisher’s 135 exact test, p < 0.001) more frequently tetraploid (68%) than sourdough strains (35%). On the 136 other hand, we did not observe any significant difference in ploidy distribution between the 137 198 sourdough strains isolated in Belgium, France and Italy (two sided Fisher’s exact test, P 138 > 0.05, Table 2). 139 To study whether tetraploidy promoted the adaptation of S. cerevisiae to a bakery 140 environment, competition experiments between tetraploid and diploid strains were carried 141 out in synthetic sourdough media. Commercial and sourdough strains of each ploidy level 142 (Table S2) were included in the analysis to test not only the effect of ploidy but also the 143 effect of commercial/sourdough origin. No evidence of gain for tetraploids was found

144 (t43=-1,4288, P=0.16, Figure 1). To test whether tetraploids provide a benefit for bakers’ 145 practices, the effect of ploidy on fermentation kinetics was then analyzed. There was no

146 significant effect of ploidy level on the maximum cumulative CO2 production released at the

147 end of fermentation (CO2max, F1,68=0.1, P=0.749), maximum CO2 production rate (Vmax,

148 F1,68=0.62, P=0.434) and time at Vmax (tVmax, F1,68=0.067, P=0.797) parameters 149 (Figure 2A,C,D). By contrast, there was a significant effect of ploidy on the latency phase

150 of CO2 production (time necessary to release 1g of CO2; F1,68= 7.01, P=0.01), while no

151 significant effect of the origin of the (sourdough/commercial) was found (F1,68= 3.48, 152 P=0.07). On average, tetraploids started fermentation earlier than diploids (Figure 2B).

153 Bakery strains are polyphyletic and present admixture

154 The evolutionary history of bakery strains was first studied on diploids using . We 155 examined the genomes of 68 bakery S. cerevisiae strains that included 17 newly sequenced bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 156 diploid sourdough strains and a representative set of 51 previously sequenced bakery strains 157 (Table S5). We studied the population structure of bakery strains based on 33,032 biallelic 158 SNPs using fastStructure (Figure 3). This analysis yielded a most-likely population structure 159 with 6 groups (likelihood -0.756). Groups P3 and P4 both contained sourdough strains, with 160 a minority of other strains however for group P4. On the other hand, groups P2 and P6 were 161 mostly composed of commercial strains. Finally, groups P1 and P5 comprised both 162 sourdough and commercial strains. This genetic structuration was also observed using 163 DAPC, which do not rely on any -history traits and evolutionary assumptions 164 (Figure S1) and on a maximum-likelihood phylogenetic tree (Figure 4), except for five 165 strains that clustered on one side of the tree, outside of their group defined by fastStructure. 166 Overall, there was no clustering according to the country of origin of the strains. 167 We then analyzed the genetic relationship of bakery strains with the previously analysed 168 1,011 worldwide collection of S. cerevisiae [12]. Adding extra bakery genomes to the 1,011 169 genomes tree did not change the clustering defined in [12] (Figure 5). The bakery 170 strains/genomes were distributed between the “Wine/European”, “African beer”, “Mixed 171 origin”, “Mosaic region 3”, “Asian fermentation”, and “Mosaic region 1” clades. The P1 172 bakery group defined by fastStructure (7 bakery strains) was included in the 173 “Wine/European” clade, while group P5 (3 bakery strains) was found in the “African beer” 174 clade. The bakery groups P2 and P6 (23 strains, 7 from sourdough) were both located within 175 the ”Mixed origin” clade that also included beer strains, clinical strains, and strains isolated 176 from water, fruits, tree leaves and natural environment. These two groups are indeed closely 177 related and were not distinguished by fastStructure when the number of assumed ancestral 178 groups K equalled 4 (Figure 3). Finally, the bakery groups P3 and P4 (19 strains, 16 from 179 sourdough) were located within a group of mosaic strains that includes strains isolated from 180 wine, sake, insect, palm wine, fruit, or clinical, fermentation, distillery, natural environment. 181 These two groups are also closely related and were not distinguished when K equalled 5 182 (Figure 3). 183 To analyse the degree of admixture of bakery strains, we ran Admixture on the bakery 184 genomes as well as on 90 genomes chosen across the 1,011 genomes tree clades [12]. The 185 strains were chosen among all the clades except those not found to contribute to the bakery- 186 strains containing clades (Figure 6, Table S6). A total of 48 bakery strains out of 68 187 presented some level of admixture varying between strains, and reaching up 70% of the 188 genome. For a single strain, from 2 to 11 ancestral populations were admixed. There was 189 evidence of admixture between bakery strains of “Mosaic region 3” and “Mixed origin” 190 clades. In addition, there was evidence of admixture with other clades and contributors were 191 found to belong to the genetic clades “Asian fermentation”, “Wine/European”, “Ale beer”, 192 “Brazilian bioethanol”, “Mosaic beer” and “African beer”. One contributor however could 193 not be identified, suggesting the presence of an extinct or otherwise uncharacterized bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 194 S. cerevisiae population. Novel alleles derived from unknown or extinct populations were 195 also found in ale beer strains (Fay et al. 2019). The high degree of admixture suggested that 196 dispersion and hybridization were parts of the main drivers of bakery strains evolution. 197 The bakery strains of the “Mixed origin” and “Mosaic region 3” clades differed by the 198 origin of some introgressions. Introgression from the “Ale beer” clade was only detected in 199 commercial and sourdough strains of the “Mixed origin” clade (28% of the “Mixed origin” 200 bakery strains; Figure 6). Introgression from the “Asian fermentation” population was only 201 found in bakery strains of the “Mosaic region 3” clade (60% of the “Mosaic region 3” 202 bakery strains; Figure 6). This last result was confirmed by an analysis with Treemix [45] 203 that evidenced a gene flow between “Asian fermentation” and “Mosaic region 3” bakery 204 populations (w = 38%, three-population f3 test, Z = -27; Figure S2).

205 An increased copy number of maltase and isomaltase, transporter and 206 regulator genes in the sourdough strains clade

207 Large copy number variations were previously detected in S. cerevisiae [12]. We analysed 208 large CNV on our bakery strains (Table S7) and found that twenty-six strains (40%) 209 displayed major chromosomal rearrangements or aneuploidies. Chromosome 9 was the most 210 affected by CNV (10 strains out of 26). In addition, we analyzed the copy number of genes 211 involved in maltose, iso-maltose and assimilation. These carbohydrates are common 212 in cereal products which may have led to the selection of an increased number of genes 213 involved in their assimilation in bakery strains. Gene copy number was compared between 214 bakery and non-bakery strains within each clade containing bakery strains to eliminate the 215 genetic structuration bias (Figure S3). Analysis was first performed on the MAL maltose 216 gene cluster [46,47]. In S. cerevisiae, the maltose gene cluster is composed of three genes, 217 encoding the maltose transporter (permease, MAL1), maltase (MAL2) and transcription 218 regulator (MAL3). The genes involved in maltose utilization are represented in five well- 219 described MAL loci located on subtelomeric regions [46,47]. The presence of just one MAL 220 locus is sufficient to allow for maltose fermentation [48,49]. In the “Mosaic region 3” clade, 221 where most bakery strains were isolated from sourdough, the number of copies of the 222 MAL12 (Wilcoxon rank sum test, p-value < 10-3) and MAL32 (p-value < 10-4) maltase genes 223 was on average significantly higher in bakery strains than in non-bakery strains 224 (Figure S3A,B). The same was observed for the maltose permease gene MAL31 (p-value < 225 10-4). The same analysis was then performed for the isomaltase genes (Figure S3C). A 226 significant increase in copy number for IMA1 (p-value < 10-6), IMA3 (p-value < 10-4) and 227 IMA4 (p-value < 10-4) in bakery strains compared to non-bakery strains was also observed in 228 the “Mosaic region 3” clade. In the “Mixed origin” clade where many commercial bakery 229 strains were located, we did not detect any increase in of copy number for genes in the bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 230 maltose and isomaltose gene clusters in bakery strains compared to others. These results 231 suggest selection for a better assimilation of maltose and isomaltose in sourdough, where 232 starch degradation release maltose. In the same way, adaptation to beer environment was 233 found to be associated to an increased copy number of the maltase gene cluster [50].

234 Phenotypic signatures of domestication

235 To test further whether sourdough strains have undergone human selection, we compared 236 fermentation performance between bakery and non-bakery strains and analyzed phenotypic 237 convergence among bakery strains. Fourteen sourdough strains, six commercial strains and 238 six non-bakery strains of diverse origins and genetic groups were fermented in a synthetic 239 sourdough medium (Table S8). As previously, four fermentation parameters relevant to

240 bread-making were studied: time necessary to release 1g of CO2, the maximum cumulative

241 CO2 production released at the end of fermentation (CO2max), maximum CO2 production 242 rate (Vmax) and time at Vmax (tVmax). In addition, the number of cells after 27h of 243 fermentation was used as proxy for absolute fitness. We found that non-bakery strains had

244 significantly lower maximum cumulative CO2 production, lower maximum CO2 production 245 rate and started fermentation later than sourdough and commercial bakery strains (Table S9, 246 Figure 7) showing that both sourdough and commercial strains have been selected for better 247 performance in fermentation. Commercial bakery strains performed better than sourdough

248 strains in terms of fermentation onset and CO2 production. However, sourdough strains had a

249 maximum CO2 production rate as high as commercial strains. Moreover, sourdough strains 250 reached a significantly higher population size than commercial strains suggesting they 251 display increased fitness in a synthetic sourdough medium compared to industrial yeasts 252 (Figure S4). Overall, these results confirmed that sourdough strains were domesticated by 253 artisanal and farmer-bakers and are better adapted to their environment than other strains.

254 Genetic relationships between diploids and tetraploids

255 To analyse the genetic relationship between diploids and tetraploids, we studied genetic 256 diversity in 229 bakery strains (31 commercial and 198 isolated from sourdough; Table S1) 257 with 15 microsatellite markers. A total of 31 strains were analyzed using both microsatellites 258 and genomic sequences, which allowed the comparison of genomic and microsatellite data. 259 The microsatellite genetic relatedness tree based on the Ritland relatedness coefficient [51] 260 showed a clustering concordant with the genomic groups (Figure 8). Commercial strains 261 clustered in groups P2 and P6 while sourdough strains were scattered all over the tree. 262 Groups P3 and P4, mostly represented by sourdough strains, contained mostly diploids (76 263 diploids strains and 5 tetraploids strains) while groups P2 and P6 contained mostly bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 264 tetraploids. Genotypes were clustered according to the sourdough from which they have 265 been isolated. Strains from the same sourdough were either all diploids (sourdoughs B9b, 266 Al) or all tetraploids (sourdough F). Interestingly two sourdoughs (B9c, B10L) contained 267 both diploids and tetraploids. In one case, there was one tetraploid and seven diploids. In the 268 other case, there was four diploids and 9 tetraploids. The diploids and tetraploids were very 269 closely related suggesting they derived from each other rather than from different 270 introduction events. 271 Further analysis of population structure using an Analysis of Molecular Variance (AMOVA) 272 [52] allowed the joined analysis of diploids and tetrapoids [53]. First, we studied the 273 differences between bakery origin (commercial vs sourdough strains). Only 11% of the 274 variation was found between bakery origins (Table S10) while the variation within bakery 275 origin was 89%. However, there was a significant structuration by bakery origin 276 (permutation test p-value < 10-3), confirming the genomic and microsatellite clustering of 277 most sourdough strains on one side and most commercial strains on the other. Then we 278 focused on sourdough strains isolated in France, Belgium and Italy and examined whether 279 there was any geographical structuration of sourdough strains according to their country of 280 origin. To avoid unequal sampling between country, three strains per sourdough were 281 randomly sampled. Most of the variance arose within each country (89%). However, a 282 permutation test revealed significant differentiation between countries (permutation test p- 283 value < 10-3). Significant differentiation between countries and similar distribution of 284 variation were also found when all analyzed strains from France, Italy and Belgium were 285 included. Finally, the distribution of genetic diversity within and between sourdoughs was 286 analyzed for France, where a large number of yeast strains per sourdough were available. 287 Most of the observed variance occurred between sourdoughs (76%), showing that genetic 288 variation between sourdoughs exceeded within sourdough. Permutation 289 tests revealed a significant structuration according to the sourdough of origin (simulated p- 290 value < 10-3). However, some intra-genetic sourdough diversity was also found as for 291 example in sourdough B9b and Al, where a strain (B9b, Al28) clustered far from most of the 292 strains of the sourdough revealing a dispersion event. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

293 Discussion

294 We report here the first broad analysis of bakery yeast domestication using a collection of 295 229 Saccharomyces cerevisiae bakery strains collected worldwide from industry or natural 296 sourdoughs. We found that the origin of bakery strains is polyphyletic. Most bakery strains 297 clustered in two main clades, suggesting that bakery strains have undergone at least two 298 main domestication trajectories: one domestication trajectory appeared to have led to most 299 commercial strains, while the other led to sourdough strains. 300 The domestication of commercial bakery strains was associated with at least one 301 tetraploidization event and the selection for a shorter latency phase of fermentation. To our 302 knowledge, this is the first time that selection and dispersion of widespread autotetraploids 303 are associated with the domestication of fungi. Beer strains of S. cerevisiae were found to 304 have a high rate of ploidy variation associated in addition to aneuploidy, but there was no 305 evidence of worldwide spread of autotetraploids [12,50]. A change in chromosomal copy 306 number is often observed in yeast whenever they adapt to new, stressful environments 307 [44,54,55]. However, several studies showed genome instability in yeast polyploids. 308 Chromosome loss, aneuploid mis-segregation event, chromosome translocation, and large 309 chromosome rearrangement all occurred during the evolution of yeast polyploids [44]. 310 results showed that tetraploid ancestors converged into diploids in 311 1800 mitotic generations [56,57]. Here we found that the vast majority of commercial yeasts 312 are autotetraploid as are also some strains isolated from sourdough. Bakery autotetraploids 313 are in with diploids and thus represent a new species (Albertin et al. 314 2009). The high proportion of tetraploids among commercial strains as well as the 315 association of tetraploids with shorter fermentation latency phase suggest that deliberate 316 artificial selection by industrial yeast geneticists could be at the origin of tetraploid bakery 317 strains and that worldwide industrial distribution of these selected strains might have 318 disseminated tetraploids in bakery environments. The high level of aneuploidy observed in 319 bakery strains could result from the known instability of tetraploid genomes. 320 The domestication of sourdough strains was associated with an increase in copy number of 321 the maltose and isomaltose transporter (permease) and maltase, isomaltase transcription 322 regulator encoding genes. While CNVs are generally deleterious, they also appear to be a 323 key mechanism that can enable adaptation during an episode of stringent selection. CNVs 324 are widespread in domesticated plant and animal species [58] as well as in domesticated 325 yeast populations (Legras and Sicard, 2011; Steensels et al. 2018). Because maltose and 326 isomaltose are released through amylolytic starch breakdown, they represent an important 327 carbon source in dough and may directly be linked to fermentation performance (duration

328 and CO2 production). Therefore, natural selection in sourdough as well as unintentional bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 329 selection by bakers for increased fermentation rate may both have selected for strains having 330 an increased copy number of genes related to maltose and isomaltose utilization. A slight but 331 significant geographic structuration of the genetic diversity was found according to 332 sourdough and its country of origin suggesting an effect of bakery practices and 333 environments. 334 Some sourdough strains were found in the commercial strains”Mixed origin” clade, and 335 vice versa, suggesting that commercial starters may disseminate in natural sourdoughs. Some 336 bakers may indeed add commercial starter to their sourdough or may contaminate their 337 sourdough by using commercial yeast in the bakery house for making other bakery products 338 such as pastries. Admixture between these two clades was also detected, suggesting gene 339 flow occurrence between commercial and sourdough strains. 340 Bakery strains have been hypothesized to be genetically related to beer strains (Legras et al. 341 2007, Gallone et al. 2016). In the XVIIth century, baker’s yeast was reportedly provided by 342 brewers [4]. Yet, although beer strains were found in seven clades out of the 26 clades 343 structuring the 1,011 S. cerevisiae worldwide strain collection [12], only two of these clades 344 also contained bakery’s strains. First, the African beer clade contains sourdough strains 345 isolated from dough coming from Ghana, suggesting that the same strains are used 346 both to ferment maize dough and to brew beer. Second, the ”Mixed origin” clade contains 347 beer strains, commercial bakery strains from all over the world, a few sourdough strains 348 from Belgium and France as well as strains from diverse other habitats (fruits, soil, water, 349 humans, …). None of the bakery strains clustered with the “Ale beer” clades. However, 350 some introgression from the Ale beer clade was detected in ten out of the 36 bakery strains 351 of the ”Mixed origin” clade indicating the presence of some gene flow between “Ale beer” 352 and bakery strains. This clade mostly contained commercial strains suggesting that some Ale 353 beer strains have been used as progenitors in the industrial breeding of bakery strains. 354 A previous study also proposed that bakery strains could originate from a tetraploidization 355 event between ale beer and wine strains [16]. Moreover, a recent study found that ale beer 356 strains were derived from admixture between populations closely related to European 357 wine strains and Asian rice wine strains [59]. Here, all bakery strains but three clustered 358 separately from the well-defined wine and sake lineages, clearly suggesting a distinct 359 evolutionary history. The admixture analysis provided no evidence of gene flow between 360 bakery and sake strains. However, there was evidence of small introgression from wine 361 populations and from “Asian fermentation” populations. Interestingly, sign of introgression 362 from wine populations were found both in sourdough and commercial strains while 363 introgressions from “Asian fermentation” populations were detected only in sourdough 364 strains (Figure 4). Artisanal bakers often experiment other fermentation processes, among 365 which “Asian fermentation”, which may explain this finding. 366 Sourdough is a human-made habitat. One may consider that any yeast population originating bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 367 from sourdough is domesticated since this environment would not exist without human 368 intervention. Alternatively, one may consider that sourdough yeast populations can only be 369 considered domesticated if some human selection has indeed occurred. Here, we provided 370 evidence that sourdough strains are not only present in their environment by chance or by 371 recurrent introduction but have been selected for better fermentation performance. They

372 compared to commercial strains in terms of maximum CO2 production rate but reached a 373 higher population size at the end of fermentation. These results suggested that sourdough 374 strains are better adapted to a sourdough environment and provided interesting genetic 375 resources for improving sourdough bread making process. 376 In summary, our study revealed that bakery strains have undergone at least two main 377 domestication trajectories that mobilized different genetic events (tetraploidization, CNV), 378 and selection targets (shortened latency phase of fermentation in industry, adaptation to 379 maltose utilization and sourdough environment in artisanal bakery). We also showed that 380 dispersion and gene flow is an important driver of bakery strains evolution and that different 381 sources of introgression have occurred in sourdough and commercial strains (respectively 382 “Asian” and “Ale beer” sources). Overall, this is the first time that the analysis of fungal 383 domestication revealed that artisanal and industrial domestication led to divergent 384 populations. This demonstrates the need of conserving different fermentation practices to 385 maintain microbial genetic diversity. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

386 Materials and Methods

387 Yeast collection and cultivation procedure

388 The collection of strains analysed is presented on Tables S1, S5, S8. One hundred and 389 twenty-nine strains were collected from sourdoughs in France as previously described 390 [42,60]. Twenty sourdough strains from Belgium isolated by [61] were kindly provided by 391 the Belgium MUCL collection. Finally, 47 sourdough strains isolated by [62] in Italy were 392 kindly provided by Fabio Minervini through the University of Perugia yeast collection 393 (Minervini et al. 2012) and two sourdough strains from Sicily were kindly provided by Jean- 394 Luc Legras [19]. Thirty-one commercial strains were ordered from different international 395 yeast collection or bought as starters. 396 Cultures were performed in 10 mL of liquid YE medium and were inoculated with yeast 397 cells either from frozen stocks (stored at -80 °C) or by picking a single colony from a 398 previous culture plate.

399 Ploidy analysis by flow cytometry

400 Strain ploidy was analyzed by flow cytometry. Namely, 107 yeast cells, recovered at the 401 beginning of stationary phase, were fixed in 70% for 16 h at 4 °C. They were washed 402 with 200 μL sodium citrate buffer (50 mM, pH 7) and then dispersed in 1 mL of the sameL sodiumcitratebuffer(50mM,pH7)andthendispersedin1mLofthesame 403 buffer. 100 μL sodium citrate buffer (50 mM, pH 7) and then dispersed in 1 mL of the sameL ofcellsuspensionweretransferredtoamicrotubeandtreatedwith1μLsodiumcitratebuffer(50mM,pH7)thendispersedinmLthesameL 404 RNAse A (100 mg/mL) for 2 h at 37 °C. Labelling was performed by addition of 400 μL sodium citratebuffer(50mM,pH7)andthendispersedin1mLofthesameL 405 a staining solution (50 μL sodium citrate buffer (50 mM, pH 7) and then dispersed in 1 mL of thesameg/mLpropidiumiodideincitratebuffer),andincubatingfor40min 406 at 20 °C in the dark. Cells were recovered by centrifugation and resuspended in 500 μL sodiumcitratebuffer(50mM,pH7)andthendispersedin1mLofthesameL 407 citrate buffer. 408 Flow cytometry analysis of 30,000 cells was carried out using the MACSQuant® Analyzer 409 from Miltenyi Biotec GmbH (Germany) and the data analysis by the MACSQuant® 410 software. A haploid strain (S288C) and a tetraploid strain (Levante; (W. Albertin et al. 411 2009)) were used as calibration controls.

412 Fitness and fermentation analysis

413 GFP labelling

414 To study the impact of ploidy and strain origin (sourdough/commercial) on fitness, three 415 diploid and three tetraploid strains were tagged with GFP. The pFA6a-TEF2Pr-eGFP- 416 ADH1-NATMX4 plasmid [63] was used as a template to amplify a cassette containing the bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 417 TEF2 promoter, eGFP, ADH1 terminator and NATMX4 conferring resistance to clonNat. 418 The PCR fragment obtained with primers GFPNATMXtoHO-for (5’- 419 GCTATTGAGTAAGTTCGATCCGTTTGGCGTCTTTTGGGGTGTAACGCCAAGATCTGTTTAGCTTGC 420 CTTGTC-3’) and GFPNATMXtoHO-rev (5’-GAGGCCCGCGGACAGCATCAAACTGTAAGATTC 421 CGCCACATTTTATACACTCATGAATTCGAGCTCGTTGTC-3) was inserted into the HO locus of 422 the selected strains. All S. cerevisiae strains used here are listed in Table S3. The fitness and 423 fermentation cost of carrying the GFP construction was assessed by competing the GFP- 424 labelled and its unlabelled ancestral strain, as well as by comparing fermentation kinetics of 425 these two strains. Relative fitness of the GFP-labelled strain relative to the unlabelled one 426 was not significantly different from 1 (One-sample t-test, two-sided, Table S4) and neither 427 did GFP labelling change fermentation kinetics parameters (ANOVA, Table S4).

428 Competition and Fermentation conditions

429 Competition between GFP-labelled and unlabeled strains and single strain fermentations 430 kinetics were performed in a sourdough synthetic medium (SSM) that was adapted from [64] 431 to better mimic the average composition of sourdoughs. The SSM contained, per liter: wheat

432 peptone, 24 g; MgSO4.7H20, 0.2 g; MnSO4.H2O, 0.05 g; KH2PO4, 4 g; K2HPO4, 4 g; Tween 433 80, 1 mL; , 15 g; maltose, 35 g; cobalamine, 0.2 mg; folic acid, 0.2 mg; 434 nicotinamide, 0.2 mg; , 0.2 mg; pyridoxal-phosphate, 0.2 mg and thiamine, 435 0.2 mg. The pH was adjusted to 4.5 with citric acid and the solution was sterilized by steam 436 pasteurization for 15 min. Sterile-filtered vitamin and sugar solutions were added after 437 pasteurization. Overnight pre-cultures in YPD were titrated with a C6 flow cytometer 438 (Accuri, BD Biosciences). For competition experiments, 5.105 cells/mL of each strain were 439 then inoculated in 15 mL SSM medium. For single strain analysis of fermentation kinetics, 440 106 cells/mL of pre-culture were inoculated in 15 mL SSM media. 441 Fermentations were carried out at 24 °C with constant magnetic stirring (300 rpm) in 20 mL

442 glass tubes closed with a filter tip to allow release of CO2. Fermentations were monitored

443 during 24 h for CO2 release, by measuring weight loss every 40 min using an automated 444 robotic system [65]. 445 At the end of fermentation, cultures were centrifuged and pellets were resuspended in PBS 446 for flow cytometry analysis (C6 cytometer, Accuri, BD Biosciences). Population size and 447 cell viability were determined as described in [66]. Relative fitness of tetraploid vs diploid 448 strains was estimated based on the proportion of GFP-labelled vs unlabelled strains in mixed 449 cultures. GFP fluorescence (excitation 488 nm, emission 530 nm) was collected in the FL1 450 channel.

451 Statistical analysis

452 All competition and single strain fermentation were carried out with 3 or 4 replicates. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 453 Relative fitness was calculated as Af ln( ) Ai w= Bf ln( ) Bi 454 where w is fitness, A and B are the population sizes of the two competitors, while subscripts 455 i and f indicate the initial and final time point (24h) of the competition kinetics [67]. To 456 statistically compare the fitness of tetraploids and diploids, the mean relative fitness of 457 tetraploids relative to diploids was compared to 1 using a one-sample t-test, two-sided 458 (Table S4). 459 To test the effect of ploidy and strain origin (commercial/sourdough) on fermentation

460 kinetics, the cumulative CO2 production curve was calculated and the kinetics of CO2 461 production rate over time was estimated. Four parameters were then estimated: the

462 maximum CO2 release (g), the fermentation latency-phase time (h) (time between

463 inoculation and the beginning of the fermentation calculated as 1g of CO2 release), the

464 maximum CO2 production rate Vmax (g/L/h) and the time of the maximum CO2 production 465 rate. The effect of ploidy and strain origin was tested for each kinetic parameter using the

466 following linear model: Y ijk=μ + ploidyi +originj+ ploidy x originij+εijk , where Yijk is the

467 kinetics parameter variable, ai is the fixed ploidy effect, bj the fixed origin effect, gij the

468 interaction effect and εijk the residual error. 469 To test the “habitat of origin” effect (sourdough/commercial/other) on fermentation kinetics, 470 the same four kinetics parameters were estimated. The number of cells after 27h of 471 fermentation was also analyzed as a proxy of absolute fitness. The following mixed linear

472 model was used Y ijk=μ +Bloci+Strain j+origink +ε ijk , where Yijk is the fermentation

473 kinetics or population size variable, Bloci is the random bloc effect, Strainj the random strain

474 effect, origink the habitat of origin fixed effect and εijk the residual error. Tukey tests were 475 used to compare pair of means.

476 Genomic DNA extraction

477 Cells from an overnight culture were recovered by centrifugation of 5 mL of culture medium 478 at 4500 rpm for 3 min. The yeast pellet was suspended in a sorbitol solution containing 20 479 μL sodium citrate buffer (50 mM, pH 7) and then dispersed in 1 mL of the sameL Zymolyase 20T(1mg/mL).Cellwalllysiswasperformedat37°Cfor1h.DNA 480 extraction was carried out using the DNAeasy Blood & Tissue Kit (Qiagen).

481 Microsatellite typing and analysis

482 In order to study the genetic diversity of diploid and tetraploid, 15 microsatellites loci 483 previously described in [68] were used: C3, C4, C5, C6, C8, C9, C11, ScAAT1, ScAAT3, bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 484 SCYOR267C, YKL172w, YKR072c, YLL049, YLR, YPL009c. Multiplexing was used in 485 order to amplify 4 or 5 microsatellites per PCR run, with two distinct markings, one at 700 486 nm and the second at 800 nm. Once amplified, amplicons were diluted 1/20 in formamide, 487 denatured for 5 minutes at 85 °C, then separated by electrophoresis on a 13 % 488 polyacrylamide gel containing 39 % in 1.2X TBE buffer at 2000 V for 15 h (50 °C) on 489 an automatic sequencer. 490 Analyses of microsatellite data were performed using Poppr version 2.8.2 [69]. A 491 microsatellite genetic relatedness tree was constructed based on the Ritland relatedness 492 coefficient [51]. Analysis of Molecular Variance (AMOVA) was used as a method of 493 estimating population differentiation (Excoffier, Smouse, et Quattro 1992).

494 Genome sequencing and read processing

495 Genome sequencing data were obtained for 68 yeast strains from numerous sources 496 according to Table S2. For the present study, 17 yeast genomes were newly sequenced in 497 our laboratory: DNA samples were processed to generate libraries of short 400-bp inserts. 498 After passing quality control, the libraries were sequenced using an Illumina HiSeq 2000 499 platform. Sequencing from both ends generated paired-end reads of 2 x 100 bp, resulting in 500 an average sequencing depth of 100X. This dataset was deposited in the European 501 Nucleotide Archive (ENA) under study accessions PRJEB36058. Trimming low quality 502 regions and adapters in Illumina data was performed using Trimmomatic version 0.322 [70]

503 with sequencing parameters: ILLUMINACLIP:adapterFile:2:30:7, LEADING:20, 504 TRAILING:20, SLIDINGWINDOW:20:25, MINLEN:75.

505 Variant calling

506 We used the Genome Analysis Toolkit (GATK) [71] version 3.6 for SNP and indel calling. 507 Briefly, the workflow is divided into four sequential steps: initial mapping, refinement of the 508 initial reads, multi-sample indel and SNP calling, and finally variant quality score 509 recalibration. 510 First, reads were aligned to the S288c reference genome (release number R64-1-1, 511 downloaded from SGD) using BWA version 0.7.12 [72] resulting in aligned reads in a BAM 512 file format. 513 Second, optical and PCR duplicates were removed using MarkDuplicate from the Picard 514 Tools version 2.6.0 (http://picard.sourceforge.net). Base quality scores were recalibrated 515 using BaseRecalibrator/PrintReads (GATK). These recalibrated scores in the output BAM 516 file are closer to their actual probability of mismatching to the reference genome, and are 517 subsequently more accurate. Moreover, the recalibration tool attempts to correct for variation 518 in quality with machine cycle and sequence context. At the end of this step we obtained bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 519 analysis-ready reads. 520 Third, we performed SNP and indel discovery using HaplotypeCaller (GATK) on each

521 sample separately in BP_RESOLUTION mode, to produce an intermediate file format termed 522 GVCF (for Genomic VCF). These per-sample GVCFs were then run through a joint 523 genotyping step using GenotypeGVCFs (GATK) to produce a raw multi-sample VCF 524 callset. 525 Fourth, we used Variant Quality Score Recalibration (VQSR) to build an adaptive error 526 model (VariantRecalibrator tool) using an unpublished dataset of known SNPs and Indels 527 obtained from 86 genomes [19]. Then this model was applied (ApplyRecalibration tool) to 528 estimate the probability that each variant in the callset is a true genetic variant or a machine / 529 alignment artifact. This step assigns a VQSLOD score to each variant that is much more 530 reliable than the raw QUAL score calculated by the caller. We used this variant quality score 531 to filter the raw call set, thus producing a subset of calls with our desired level of quality, 532 fine-tuned to balance specificity and sensitivity. This genotyping pipeline resulted in VCF 533 file containing 302,290 biallelic SNPs and 21,045 indels discovered across 68 samples to 534 which were associated a genotyping quality for each strain.

535 Population structure

536 The set 302,290 biallelic SNPs sites identified above was further filtered by removing SNPs 537 with missing genotypes above 0.10, minimum alternate allele frequency (MAF) below 0.03 538 and SNPs in linkage-disequilibrium using PLINK [73] version 1.9-beta3j with a window size 539 of 50 SNPs, a step of 5 SNPs at a time and a r2 threshold of 0.5. The resulting filtered dataset 540 contained 32,379 SNPs positions. 541 Twenty independent runs of fastStructure version 1.0 [74] were performed varying ancestral 542 population from 1 to 10 using the simple prior. The number of iterations varied from 10 (K = 543 1) to 70 (K = 10). The highest likelihood was obtained for the solution at 6 ancestral 544 populations (likelihood: -0.75599; total iterations: 30). CLUMPAK [75] was used for 545 analyzing the result of multiple independent runs of fastStructure. CLUMPAK identifies an 546 optimal alignment of inferred clusters across different values of K, simplifying the 547 comparison of clustering results across different K values. Structure plots were obtained 548 using the interactive web application Structure Plot [76]. 549 Structuration was also studied using discriminant analysis of principal components (DAPC) 550 [77] a multivariate method designed to identify clusters of genetically related individuals. 551 This analysis was performed using the R package adegenet version 2.1.1 [78]. DAPC was 552 performed (function dapc) using clusters defined by K-means where we specified a number 553 of clusters from 4 to 7. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 554 Phylogenetic tree imputation

555 The set of 302,290 biallelic SNPs sites was filtered by removing SNPs at positions with 556 missing genotypes above 0.10 and minimum alternate allele frequency (MAF) below 0.10. 557 The resulting filtered dataset containd 99,128 SNPs positions. The VCF file was converted

558 into Fasta sequences using generate_snp_sequence.R from the R-package SNPhylo [79]. 559 A phylogenetic tree was computed with RAxML version 7.2.8 [80] performing a complete

560 analysis (ML search + 100 bootstrapping) using the GTRGAMMA evolution model. 561 For the microsatellite typing obtained from 229 baker yeasts, Ritland relatedness coefficient 562 [51] was estimated using PolyRelatedness, a software able to estimating pairwise relatedness 563 between individuals with different levels of ploidy [81]. A neighbor joining tree was 564 obtained using the nj function from the ape R package.

565 Analysis across the 1,011 genomes data

566 A genotyping matrix was constructed with the GenotypeGVCFs function of GATK that was 567 run with 1,011 gvcf files constructed in [12] as well as the 26 bakery strains gvcf files that 568 were not included in this previous study (17 newly sequenced diploid sourdough strains 569 genomes and a 9 previously sequenced bakery strains). This extended the dataset to a total of 570 68 bakery yeast genomes. 571 The neighbor-joining tree was constructed with the R packages ape and SNPrelate. The gvcf 572 matrix was first converted into a gds file and individual dissimilarities were estimated for 573 each pair of individuals with the snpgdsDiss function. The bionj algorithm was then run on 574 the distance matrix that was obtained. 575 A set of 552,093 biallelic SNPs was obtained from the gvcf matrix selecting 157 genomes 576 (including 68 bakery strains; Table S6). SNPs were further filtered by removing SNPs with 577 missing genotypes above 0.10, minimum alternate allele frequency (MAF) below 0.03 and 578 SNPs in linkage-disequilibrium using PLINK version 1.9-beta3j with a window size of 50 579 SNPs, a step of 5 SNPs at a time and r2 threshold of 0.5. The resulting filtered dataset 580 contains 49,482 SNPs positions. Twenty independent runs of Admixture version 1.3.0 [82] 581 were performed varying ancestral population from 2 to 20. The value of K = 17 exhibited the 582 lowest cross-validation error compared to other K values. CLUMP [83] was used for 583 analysis the results of multiple independent runs of Admixture. Structure plots were obtained 584 using the interactive web application Structure Plot [76]. 585 To evaluate the bakery strains admixture, we also used the TreeMix algorithm [45], which 586 builds population trees and tests for the presence of gene flow between populations. We 587 estimated a maximum-likelihood tree (Figure S2) rooted using the China population 588 (CHNV), the likely ancestral population of S. cerevisiae [13]. To test for gene flow, we used 589 the three-population f3 test [84] as suggested by [45]. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

590 Fundings

591 This research was partly funded by Agence Nationale de la Recherche grant (ANR-13- 592 ALID-0005 BAKERY, France).

593 Acknowledgments

594 We acknowledge Pierre Gomes for curation of microsatellite data, a panel of bakers and 595 farmer-bakers for providing sourdoughs, F. Minervini and the university of Perugia for 596 providing Italian sourdough strains as well as all the international yeast collections for 597 providing strains. We are also grateful to Agnes Masquin and Isabelle Delmas for their 598 administrative support and Jean-Luc Legras for discussion and critical reading of the 599 manuscript.

600 Author contributions

601 D.Si. supervised the project and designed the experiment; F.B., T.N. and D.Si. analyzed the 602 data and wrote the manuscript. D.Se. performed fitness experiments and conducted 603 fermentation in synthetic medium; T.N. and D.Si. performed statistical analysis on fitness 604 and fermentation data; S.G. was in charge of the yeast collection and genomic DNA 605 extraction for sequencing; L.H., N.A. and A.B. performed microsatellite typing and 606 cytometry analysis; F.B. and A.F. performed genomes analysis.

607 Competing interests

608 The authors declare no competing interest bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

609 Bibliography

1. McGovern, P.E., Zhang, J., Tang, J., Zhang, Z., Hall, G.R., Moreau, R.A., Nuñez, A., Butrym, E.D., Richards, M.P., Wang, C., et al. (2004). Fermented beverages of pre- and proto-historic China. Proc. Natl. Acad. Sci. 101, 17593–17598. Available at: https://www.pnas.org/content/101/51/17593 [Accessed January 7, 2020].

2. Gibbons, J.G., and Rinker, D.C. (2015). The genomics of microbial domestication in the fermented food environment. Curr. Opin. Genet. Dev. 35, 1–8. Available at: http://www.sciencedirect.com/science/article/pii/S0959437X15000787 [Accessed January 14, 2020].

3. Steensels, J., Gallone, B., Voordeckers, K., and Verstrepen, K.J. (2019). Domestication of Industrial Microbes. Curr. Biol. 29, R381–R393. Available at: http://www.sciencedirect.com/science/article/pii/S0960982219304233 [Accessed January 14, 2020].

4. Sicard, D., and Legras, J.-L. (2011). Bread, beer and wine: Yeast domestication in the Saccharomyces sensu stricto complex. C. R. Biol. 334, 229–236. Available at: http://www.sciencedirect.com/science/article/pii/S1631069110003057 [Accessed January 14, 2020].

5. Brüssow, H. (2020). Bioarchaeology: a profitable dialogue between microbiology and archaeology. Microb. Biotechnol. 13, 406–409. Available at: https://sfamjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1751-7915.13527 [Accessed March 25, 2020].

6. Aouizerat, T., Gutman, I., Paz, Y., Maeir, A.M., Gadot, Y., Gelman, D., Szitenberg, A., Drori, E., Pinkus, A., Schoemann, M., et al. (2019). Isolation and Characterization of Live Yeast Cells from Ancient Vessels as a Tool in Bio-Archaeology. mBio 10. Available at: https://mbio.asm.org/content/10/2/e00388-19 [Accessed March 25, 2020].

7. Salque, M., Bogucki, P.I., Pyzel, J., Sobkowiak-Tabaka, I., Grygiel, R., Szmyt, M., and Evershed, R.P. (2013). Earliest evidence for cheese making in the sixth millennium bc in northern Europe. Nature 493, 522–525. Available at: https://www.nature.com/articles/nature11698 [Accessed March 25, 2020].

8. Gibbons, J.G., Salichos, L., Slot, J.C., Rinker, D.C., McGary, K.L., King, J.G., Klich, M.A., Tabb, D.L., McDonald, W.H., and Rokas, A. (2012). The Evolutionary Imprint of Domestication on Genome Variation and Function of the Filamentous Fungus Aspergillus oryzae. Curr. Biol. 22, 1403–1409. Available at: http://www.sciencedirect.com/science/article/pii/S0960982212005866 [Accessed April 1, 2020].

9. Ropars, J., Rodríguez de la Vega, R.C., López-Villavicencio, M., Gouzy, J., Sallet, E., Dumas, É., Lacoste, S., Debuchy, R., Dupont, J., Branca, A., et al. (2015). Adaptive Horizontal Gene Transfers between Multiple Cheese-Associated Fungi. Curr. Biol. 25, 2562–2569. Available at: http://www.sciencedirect.com/science/article/pii/S0960982215009963 [Accessed April 1, 2020].

10. Dumas, E., Feurtey, A., Vega, R.C.R. de la, Prieur, S.L., Snirc, A., Coton, M., Thierry, A., Coton, E., Piver, M.L., Roueyre, D., et al. Independent domestication events in the blue-cheese fungus Penicillium roqueforti. Mol. Ecol. n/a. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.15359 [Accessed April 1, 2020]. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 11. Goddard, M.R., and Greig, D. (2015). Saccharomyces cerevisiae: a nomadic yeast with no niche? FEMS Yeast Res. 15. Available at: https://academic.oup.com/femsyr/article/15/3/fov009/545611 [Accessed January 14, 2020].

12. Peter, J., Chiara, M.D., Friedrich, A., Yue, J.-X., Pflieger, D., Bergström, A., Sigwalt, A., Barre, B., Freel, K., Llored, A., et al. (2018). Genome evolution across 1,011 Saccharomyces cerevisiae isolates. Nature 556, 339–344. Available at: https://www.nature.com/articles/s41586-018-0030-5 [Accessed December 18, 2019].

13. Wang, Q.-M., Liu, W.-Q., Liti, G., Wang, S.-A., and Bai, F.-Y. (2012). Surprisingly diverged populations of Saccharomyces cerevisiae in natural environments remote from human activity. Mol. Ecol. 21, 5404–5417. Available at: https://onlinelibrary.wiley.com/ doi/abs/10.1111/j.1365-294X.2012.05732.x [Accessed January 7, 2020].

14. Duan, S.-F., Han, P.-J., Wang, Q.-M., Liu, W.-Q., Shi, J.-Y., Li, K., Zhang, X.-L., and Bai, F.-Y. (2018). The origin and adaptive evolution of domesticated populations of yeast from Far East Asia. Nat. Commun. 9, 1–13. Available at: https://www.nature.com/ articles/s41467-018-05106-7 [Accessed April 1, 2020].

15. Liti, G., Carter, D.M., Moses, A.M., Warringer, J., Parts, L., James, S.A., Davey, R.P., Roberts, I.N., Burt, A., Koufopanou, V., et al. (2009). Population genomics of domestic and wild yeasts. Nature 458, 337–341.

16. Legras, J.-L., Merdinoglu, D., Cornuet, J.-M., and Karst, F. (2007). Bread, beer and wine: Saccharomyces cerevisiae diversity reflects human history. Mol. Ecol. 16, 2091– 2102. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365- 294X.2007.03266.x [Accessed December 19, 2019].

17. Almeida, P., Barbosa, R., Zalar, P., Imanishi, Y., Shimizu, K., Turchetti, B., Legras, J.- L., Serra, M., Dequin, S., Couloux, A., et al. (2015). A population genomics insight into the Mediterranean origins of wine yeast domestication. Mol. Ecol. 24, 5412–5427. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.13341 [Accessed January 14, 2020].

18. Marsit, S., Mena, A., Bigey, F., Sauvage, F.-X., Couloux, A., Guy, J., Legras, J.-L., Barrio, E., Dequin, S., and Galeote, V. (2015). Evolutionary Advantage Conferred by an -to-Eukaryote Gene Transfer Event in Wine Yeasts. Mol. Biol. Evol. 32, 1695–1707. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4476156/ [Accessed August 18, 2015].

19. Legras, J.-L., Galeote, V., Bigey, F., Camarasa, C., Marsit, S., Nidelet, T., Sanchez, I., Couloux, A., Guy, J., Franco-Duarte, R., et al. (2018). Adaptation of S. cerevisiae to Fermented Food Environments Reveals Remarkable Genome Plasticity and the Footprints of Domestication. Mol. Biol. Evol. 35, 1712–1727. Available at: https://academic.oup.com/mbe/article/35/7/1712/4962507 [Accessed July 4, 2018].

20. Coi, A.L., Bigey, F., Mallet, S., Marsit, S., Zara, G., Gladieux, P., Galeote, V., Budroni, M., Dequin, S., and Legras, J.L. (2017). Genomic signatures of adaptation to wine biological conditions in biofilm-forming flor yeasts. Mol. Ecol. 26, 2150–2166. Available at: http://onlinelibrary.wiley.com/doi/10.1111/mec.14053/abstract [Accessed January 15, 2018].

21. Fay, J.C., and Benavides, J.A. (2005). Evidence for Domesticated and Wild Populations of Saccharomyces cerevisiae. PLOS Genet. 1, e5. Available at: https://journals.plos.org/ plosgenetics/article?id=10.1371/journal.pgen.0010005 [Accessed January 7, 2020].

22. Barbosa, R., Pontes, A., Santos, R.O., Montandon, G.G., de Ponzzes-Gomes, C.M., bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Morais, P.B., Gonçalves, P., Rosa, C.A., and Sampaio, J.P. (2018). Multiple Rounds of Artificial Selection Promote Microbe Secondary Domestication—The Case of Cachaça Yeasts. Genome Biol. Evol. 10, 1939–1955. Available at: https://academic.oup.com/gbe/ article/10/8/1939/5047776 [Accessed March 30, 2020].

23. Gallone, B., Steensels, J., Prahl, T., Soriaga, L., Saels, V., Herrera-Malaver, B., Merlevede, A., Roncoroni, M., Voordeckers, K., Miraglia, L., et al. (2016). Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts. Cell 166, 1397-1410.e16. Available at: http://www.sciencedirect.com/science/article/pii/S0092867416310716 [Accessed September 22, 2016].

24. Gallone, B., Mertens, S., Gordon, J.L., Maere, S., Verstrepen, K.J., and Steensels, J. (2018). Origins, evolution, domestication and diversity of Saccharomyces beer yeasts. Curr. Opin. Biotechnol. 49, 148–155. Available at: http://www.sciencedirect.com/science/article/pii/S0958166917301076 [Accessed March 31, 2020].

25. Libkind, D., Hittinger, C.T., Valério, E., Gonçalves, C., Dover, J., Johnston, M., Gonçalves, P., and Sampaio, J.P. (2011). Microbe domestication and the identification of the wild genetic stock of lager- yeast. Proc. Natl. Acad. Sci. 108, 14539–14544. Available at: https://www.pnas.org/content/108/35/14539 [Accessed January 14, 2020].

26. Ludlow, C.L., Cromie, G.A., Garmendia-Torres, C., Sirr, A., Hays, M., Field, C., Jeffery, E.W., Fay, J.C., and Dudley, A.M. (2016). Independent Origins of Yeast Associated with Coffee and Cacao Fermentation. Curr. Biol. 26, 965–971. Available at: http://www.sciencedirect.com/science/article/pii/S0960982216300641 [Accessed January 14, 2020].

27. Gonçalves, M., Pontes, A., Almeida, P., Barbosa, R., Serra, M., Libkind, D., Hutzler, M., Gonçalves, P., and Sampaio, J.P. (2016). Distinct Domestication Trajectories in Top-Fermenting Beer Yeasts and Wine Yeasts. Curr. Biol. 26, 2750–2761. Available at: http://www.sciencedirect.com/science/article/pii/S0960982216309848 [Accessed March 31, 2020].

28. Dunn, B., Richter, C., Kvitek, D.J., Pugh, T., and Sherlock, G. (2012). Analysis of the Saccharomyces cerevisiae pan-genome reveals a pool of copy number variants distributed in diverse yeast strains from differing industrial environments. Genome Res. 22, 908–924. Available at: http://genome.cshlp.org/content/22/5/908 [Accessed September 19, 2017].

29. Steenwyk, J., and Rokas, A. (2017). Extensive Copy Number Variation in Fermentation- Related Genes Among Saccharomyces cerevisiae Wine Strains. G3 Genes Genomes Genet. 7, 1475–1485. Available at: https://www.g3journal.org/content/7/5/1475 [Accessed January 14, 2020].

30. Marsit, S., Sanchez, I., Galeote, V., and Dequin, S. (2016). Horizontally acquired oligopeptide transporters favour adaptation of Saccharomyces cerevisiae wine yeast to oenological environment. Environ. Microbiol. 18, 1148–1161. Available at: https://sfamjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1462-2920.13117 [Accessed March 25, 2020].

31. Albertin, W., Marullo, P., Aigle, M., Bourgais, A., Bely, M., Dillmann, C., Vienne, D.D., and Sicard, D. (2009). Evidence for autotetraploidy associated with reproductive isolation in Saccharomyces cerevisiae: towards a new domesticated species. J. Evol. Biol. 22, 2157–2170. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1420-9101.2009.01828.x [Accessed December 18, 2019]. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 32. Meirmans, P.G., Liu, S., and van Tienderen, P.H. (2018). The Analysis of Polyploid Genetic Data. J. Hered. 109, 283–296. Available at: https://academic.oup.com/jhered/article/109/3/283/4827622 [Accessed January 8, 2019].

33. Dufresne, F., Stift, M., Vergilino, R., and Mable, B.K. (2014). Recent progress and challenges in population of polyploid : an overview of current state- of-the-art molecular and statistical tools. Mol. Ecol. 23, 40–69. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.12581 [Accessed January 14, 2020].

34. Samuel, D. (1996). Investigation of Ancient Egyptian and by Correlative Microscopy. Science 273, 488–490. Available at: https://science.sciencemag.org/content/273/5274/488 [Accessed April 1, 2020].

35. Shevchenko, A., Yang, Y., Knaust, A., Thomas, H., Jiang, H., Lu, E., Wang, C., and Shevchenko, A. (2014). Proteomics identifies the composition and manufacturing recipe of the 2500-year old sourdough bread from Subeixi cemetery in China. J. Proteomics 105, 363–371. Available at: http://www.sciencedirect.com/science/article/pii/S1874391913006143 [Accessed April 1, 2020].

36. Pétel, C., Onno, B., and Prost, C. (2017). Sourdough volatile compounds and their contribution to bread: A review. Trends Food Sci. Technol. 59, 105–123. Available at: http://www.sciencedirect.com/science/article/pii/S0924224416302758 [Accessed April 4, 2020].

37. Gänzle, M.G., and Zheng, J. (2019). Lifestyles of sourdough lactobacilli – Do they matter for microbial ecology and bread quality? Int. J. Food Microbiol. 302, 15–23. Available at: http://www.sciencedirect.com/science/article/pii/S0168160518305427 [Accessed April 4, 2020].

38. Gobbetti, M., De Angelis, M., Di Cagno, R., Calasso, M., Archetti, G., and Rizzello, C.G. (2019). Novel insights on the functional/nutritional features of the sourdough fermentation. Int. J. Food Microbiol. 302, 103–113. Available at: http://www.sciencedirect.com/science/article/pii/S0168160518302770 [Accessed April 4, 2020].

39. Corsetti, A., and Settanni, L. (2007). Lactobacilli in sourdough fermentation. Food Res. Int. 40, 539–558. Available at: http://www.sciencedirect.com/science/article/pii/S0963996906001979 [Accessed February 3, 2020].

40. Carbonetto, B., Ramsayer, J., Nidelet, T., Legrand, J., and Sicard, D. (2018). Bakery yeasts, a new model for studies in ecology and evolution. Yeast 35, 591–603. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1002/yea.3350 [Accessed January 14, 2020].

41. Michel, E., Masson, E., Bubbendorf, S., Lapicque, L., Legrand, J., Guézenec, S., Nidelet, T., Marlin, T., Rué, O., Onno, B., et al. (2019). Artisanal and farmers bread making practices differently shape fungal species diversity in French sourdoughs. bioRxiv, 679472. Available at: https://www.biorxiv.org/content/10.1101/679472v1 [Accessed January 14, 2020].

42. Urien, C., Legrand, J., Montalent, P., Casaregola, S., and Sicard, D. (2019). Fungal Species Diversity in French Bread Sourdoughs Made of Organic Wheat Flour. Front. Microbiol. 10. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2019.00201/full [Accessed March 25, 2020]. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 43. Reese, A.T., Madden, A.A., Joossens, M., Lacaze, G., and Dunn, R.R. (2020). Influences of Ingredients and Bakers on the Bacteria and Fungi in Sourdough Starters and Bread. mSphere 5. Available at: https://msphere.asm.org/content/5/1/e00950-19 [Accessed February 3, 2020].

44. Albertin, W., and Marullo, P. (2012). in fungi: evolution after whole-genome duplication. Proc. R. Soc. B Biol. Sci. 279, 2497–2509. Available at: https://royalsocietypublishing.org/doi/full/10.1098/rspb.2012.0434 [Accessed February 18, 2020].

45. Pickrell, J.K., and Pritchard, J.K. (2012). Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data. PLOS Genet. 8, e1002967. Available at: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002967 [Accessed April 8, 2020].

46. Charron, M.J., Read, E., Haut, S.R., and Michels, C.A. (1989). Molecular evolution of the -associated MAL loci of Saccharomyces. Genetics 122, 307–316. Available at: https://www.genetics.org/content/122/2/307 [Accessed December 18, 2019].

47. Naumov, G.I., Naumova, E.S., and Michels, C.A. (1994). Genetic Variation of the Repeated Mal Loci in Natural Populations of Saccharomyces Cerevisiae and . Genetics 136, 803–812. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1205886/ [Accessed December 18, 2019].

48. Needleman, R.B., Kaback, D.B., Dubin, R.A., Perkins, E.L., Rosenberg, N.G., Sutherland, K.A., Forrest, D.B., and Michels, C.A. (1984). MAL6 of Saccharomyces: a complex genetic locus containing three genes required for maltose fermentation. Proc. Natl. Acad. Sci. U. S. A. 81, 2811–2815.

49. Needleman, R. (1991). Control of maltase synthesis in yeast. Mol. Microbiol. 5, 2079– 2084.

50. Gallone, B., Steensels, J., Prahl, T., Soriaga, L., Saels, V., Herrera-Malaver, B., Merlevede, A., Roncoroni, M., Voordeckers, K., Miraglia, L., et al. (2016). Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts. Cell 166, 1397-1410.e16. Available at: http://www.sciencedirect.com/science/article/pii/S0092867416310716 [Accessed September 22, 2016].

51. Ritland, K. (1996). Estimators for pairwise relatedness and individual inbreeding coefficients. Genet. Res. 67, 175–185. Available at: https://www.cambridge.org/core/journals/genetics-research/article/estimators-for- pairwise-relatedness-and-individual-inbreeding-coefficients/ 9AE218BF6BF09CCCE18121AA63561CF7 [Accessed January 21, 2020].

52. Excoffier, L., Smouse, P.E., and Quattro, J.M. (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131, 479–491. Available at: https://www.genetics.org/content/131/2/479 [Accessed July 3, 2019].

53. Meirmans, P.G., and Liu, S. (2018). Analysis of Molecular Variance (AMOVA) for Autopolyploids. Front. Ecol. Evol. 6. Available at: https://www.frontiersin.org/articles/10.3389/fevo.2018.00066/full [Accessed September 19, 2019].

54. Yona, A.H., Manor, Y.S., Herbst, R.H., Romano, G.H., Mitchell, A., Kupiec, M., Pilpel, Y., and Dahan, O. (2012). Chromosomal duplication is a transient evolutionary solution bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. to stress. Proc. Natl. Acad. Sci. 109, 21010–21015. Available at: https://www.pnas.org/content/109/51/21010 [Accessed December 19, 2019].

55. Dhar, R., Sägesser, R., Weikert, C., Yuan, J., and Wagner, A. (2011). Adaptation of Saccharomyces cerevisiae to saline stress through laboratory evolution. J. Evol. Biol. 24, 1135–1153. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1420- 9101.2011.02249.x [Accessed February 18, 2020].

56. Gerstein, A.C., Chun, H.-J.E., Grant, A., and Otto, S.P. (2006). Genomic Convergence toward Diploidy in Saccharomyces cerevisiae. PLoS Genet. 2. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1570378/ [Accessed March 31, 2020].

57. Gerstein, A.C., McBride, R.M., and Otto, S.P. (2008). Ploidy reduction in Saccharomyces cerevisiae. Biol. Lett. 4, 91–94. Available at: https://royalsocietypublishing.org/doi/full/10.1098/rsbl.2007.0476 [Accessed March 31, 2020].

58. Lye, Z.N., and Purugganan, M.D. (2019). Copy Number Variation in Domestication. Trends Plant Sci. 24, 352–365. Available at: http://www.sciencedirect.com/science/article/pii/S1360138519300159 [Accessed April 4, 2020].

59. Fay, J.C., Liu, P., Ong, G.T., Dunham, M.J., Cromie, G.A., Jeffery, E.W., Ludlow, C.L., and Dudley, A.M. (2019). A polyploid admixed origin of beer yeasts derived from European and Asian wine populations. PLOS Biol. 17, e3000147. Available at: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000147 [Accessed May 11, 2020].

60. Lhomme, E., Lattanzi, A., Dousset, X., Minervini, F., De Angelis, M., Lacaze, G., Onno, B., and Gobbetti, M. (2015). Lactic acid bacterium and yeast microbiotas of sixteen French traditional sourdoughs. Int. J. Food Microbiol. 215, 161–170. Available at: http:// www.sciencedirect.com/science/article/pii/S0168160515301288 [Accessed March 25, 2020].

61. Vrancken, G., De Vuyst, L., Van der Meulen, R., Huys, G., Vandamme, P., and Daniel, H.-M. (2010). Yeast species composition differs between artisan bakery and spontaneous laboratory sourdoughs. FEMS Yeast Res. 10, 471–481. Available at: https://academic.oup.com/femsyr/article/10/4/471/577079 [Accessed March 25, 2020].

62. Minervini, F., Lattanzi, A., Angelis, M.D., Cagno, R.D., and Gobbetti, M. (2012). Influence of Artisan Bakery- or Laboratory-Propagated Sourdoughs on the Diversity of Lactic Acid Bacterium and Yeast Microbiotas. Appl. Environ. Microbiol. 78, 5328– 5340. Available at: https://aem.asm.org/content/78/15/5328 [Accessed March 25, 2020].

63. Breslow, D.K., Cameron, D.M., Collins, S.R., Schuldiner, M., Stewart-Ornstein, J., Newman, H.W., Braun, S., Madhani, H.D., Krogan, N.J., and Weissman, J.S. (2008). A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat. Methods 5, 711–718. Available at: https://www.nature.com/articles/nmeth.1234 [Accessed April 1, 2020].

64. Vrancken, G., Rimaux, T., De Vuyst, L., and Leroy, F. (2008). Kinetic analysis of growth and sugar consumption by fermentum IMDO 130101 reveals adaptation to the acidic sourdough ecosystem. Int. J. Food Microbiol. 128, 58–66. Available at: http://www.sciencedirect.com/science/article/pii/S0168160508004339 [Accessed April 4, 2020].

65. Bloem, A., Rollero, S., Seguinot, P., Crépin, L., Perez, M., Picou, C., and Camarasa, C. (2018). Workflow Based on the Combination of Isotopic Tracer Experiments to bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Investigate Microbial Metabolism of Multiple Nutrient Sources. JoVE J. Vis. Exp., e56393. Available at: https://www.jove.com/video/56393/workflow-based-on- combination-isotopic-tracer-experiments-to [Accessed April 1, 2020].

66. Delobel, P., Pradal, M., Blondin, B., and Tesniere, C. (2012). A ‘fragile cell’ sub- population revealed during cytometric assessment of Saccharomyces cerevisiae viability in lipid-limited alcoholic fermentation. Lett. Appl. Microbiol. 55, 338–344. Available at: https://sfamjournals.onlinelibrary.wiley.com/doi/abs/10.1111/j.1472-765X.2012.03301.x [Accessed April 1, 2020].

67. Wiser, M.J., and Lenski, R.E. (2015). A Comparison of Methods to Measure Fitness in . PLoS ONE 10. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427439/ [Accessed April 4, 2020].

68. Legras, J.-L., Ruh, O., Merdinoglu, D., and Karst, F. (2005). Selection of hypervariable microsatellite loci for the characterization of Saccharomyces cerevisiae strains. Int. J. Food Microbiol. 102, 73–83. Available at: http://www.sciencedirect.com/science/article/ pii/S0168160505000474 [Accessed January 17, 2018].

69. Kamvar, Z.N., Tabima, J.F., and Grünwald, N.J. (2014). Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or . PeerJ 2, e281. Available at: https://peerj.com/articles/281 [Accessed January 17, 2018].

70. Bolger, A.M., Lohse, M., and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinforma. Oxf. Engl. 30, 2114–2120.

71. McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303. Available at: http://genome.cshlp.org/content/20/9/1297 [Accessed July 10, 2015].

72. Li, H., and Durbin, R. (2009). Fast and accurate short read alignment with Burrows- Wheeler transform. Bioinforma. Oxf. Engl. 25, 1754–1760. Available at: http://www.ncbi.nlm.nih.gov/pubmed/19451168 [Accessed September 28, 2010].

73. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M., Bender, D., Maller, J., Sklar, P., de Bakker, P., Daly, M.J., et al. (2007). PLINK: A Tool Set for Whole- Genome Association and Population-Based Linkage Analyses. Am. J. Hum. Genet. 81, 559–575. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1950838/ [Accessed April 7, 2015].

74. Raj, A., Stephens, M., and Pritchard, J.K. (2014). fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets. Genetics 197, 573–589. Available at: http://www.genetics.org/content/197/2/573 [Accessed March 9, 2017].

75. Kopelman, N.M., Mayzel, J., Jakobsson, M., Rosenberg, N.A., and Mayrose, I. (2015). Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 15, 1179–1191. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4534335/ [Accessed October 19, 2016].

76. Ramasamy, R.K., Ramasamy, S., Bindroo, B.B., and Naik, V.G. (2014). STRUCTURE PLOT: a program for drawing elegant STRUCTURE bar plots in user friendly interface. SpringerPlus 3, 431. Available at: https://springerplus.springeropen.com/articles/10.1186/2193-1801-3-431 [Accessed May 11, 2017].

77. Jombart, T., Devillard, S., and Balloux, F. (2010). Discriminant analysis of principal bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. components: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94. Available at: https://doi.org/10.1186/1471-2156-11-94 [Accessed April 14, 2020].

78. Jombart, T., and Ahmed, I. (2011). adegenet 1.3-1: new tools for the analysis of genome- wide SNP data. Bioinformatics 27, 3070–3071. Available at: https://academic.oup.com/bioinformatics/article/27/21/3070/218892/adegenet-1-3-1- new-tools-for-the-analysis-of [Accessed May 11, 2017].

79. Lee, T.-H., Guo, H., Wang, X., Kim, C., and Paterson, A.H. (2014). SNPhylo: a pipeline to construct a phylogenetic tree from huge SNP data. BMC Genomics 15, 162. Available at: https://doi.org/10.1186/1471-2164-15-162 [Accessed February 19, 2019].

80. Stamatakis, A. (2014). RAxML version 8: a tool for phylogenetic analysis and post- analysis of large phylogenies. Bioinformatics 30, 1312–1313. Available at: https://academic.oup.com/bioinformatics/article/30/9/1312/238053 [Accessed February 19, 2019].

81. Huang, K., Ritland, K., Guo, S., Dunn, D.W., Chen, D., Ren, Y., Qi, X., Zhang, P., He, G., and Li, B. (2015). Estimating pairwise relatedness between individuals with different levels of ploidy. Mol. Ecol. Resour. 15, 772–784. Available at: https://onlinelibrary.wiley.com/doi/full/10.1111/1755-0998.12351 [Accessed April 5, 2020].

82. Alexander, D.H., Novembre, J., and Lange, K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664. Available at: http://genome.cshlp.org/content/19/9/1655 [Accessed March 12, 2018].

83. Jakobsson, M., and Rosenberg, N.A. (2007). CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806. Available at: http://bioinformatics.oxfordjournals.org/content/23/14/1801 [Accessed October 20, 2016].

84. Reich, D., Thangaraj, K., Patterson, N., Price, A.L., and Singh, L. (2009). Reconstructing Indian population history. Nature 461, 489–494. Available at: https://www.nature.com/articles/nature08365/ [Accessed April 14, 2020]. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

610 Figures

611 Figure 1: Effect of ploidy on fitness. A diploid and a tetraploid strains were cultivated in 612 competition and relative fitness of 4N over 2N was computed after 24 h of fermentation in 613 synthetic sourdough medium.

614 Figure 2: Effect of ploidy on fermentation kinetics. Diploids or tetraploids were cultivated

615 in synthetic sourdough medium and CO2 released was monitored by weight loss. Four

616 parameters were then estimated: A, maximum CO2 release (g); B, fermentation latency- 617 phase time (h) (time elapsed between inoculation and the beginning of the fermentation

618 calculated as 1g of CO2 release); C, the maximum CO2 production rate Vmax (g/L/h) and D,

619 the time of the maximum CO2 production rate (h).

620 Figure 3: Population structure obtained from 33,032 biallelic SNPs from 68 bakery strains 621 using fastStructure. The vertical axis depicts the fractional representation of resolved 622 populations (colors) within each strain (horizontal axis) for K assumed ancestral populations. 623 K = 6 maximizes the marginal likelihood (-0.756) and best explains the structure.

624 Figure 4: Maximum likelihood phylogenetic tree obtained from 33,032 biallelic SNPs from 625 68 bakery strains using RAxML (evolution model: GTRGAMMA). The most likely tree 626 from 100 bootstrap replicates is presented. Groups P1-6 are defined in Figure 1.

627 Figure 5: Phylogenetic tree obtained from SNPs from strains of the S. cerevisiae 1,011- 628 genomes project (Peter et al. 2018). 17 newly sequenced diploid sourdough strains genomes 629 and a representative set of 51 previously sequenced bakery strains extended the dataset to a 630 total of 68 bakery yeast genomes (Table S5). Groups P1-6 are the same as in Figure 1. The 631 names of the clades are taken from the 1,011-genomes project as described in [12].

632 Figure 6: Population structure obtained from 48,482 biallelic SNPs from 157 genomes 633 (including 68 bakery strains; Table S6) using Admixture software. The vertical axis depicts 634 the fractional representation of resolved populations (colors) within each strain (horizontal 635 axis) for K assumed ancestral populations. The value of K = 17 exhibited the lowest cross- 636 validation error compared to other K values and best explained the structure. Groups P1-6 637 are defined in Figure 1. The clades from the 1,011-genome project are those described in 638 [12].

639 Figure 7: Phenotypic variation of fermentation kinetics in a sourdough synthetic medium bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 640 among sourdough, commercial and non-bakery strains (other). Four parameters were

641 estimated: the maximum CO2 release (g), the fermentation latency-phase time (h) (time

642 between inoculation and the beginning of the fermentation calculated as 1g of CO2 release),

643 the maximum CO2 production rate Vmax (g/L/h) and the time of the maximum CO2 644 production rate.

645 Figure 8: NJ tree computed using the Ritland coefficient of relatedness obtained from 646 microsatellite typing of the 229 bakery strains. Groups P1-6 are defined in Figure 1. Grey 647 stars indicate strains for which a genome sequence was obtained.

648 Figure S1: Structure-like plot of the probability of membership obtained from 33,032 649 biallelic SNPs from 68 bakery strains using DAPC. Function dapc was used with clusters 650 defined by K-means where we specified a number of clusters from 4 to 7. The comparison of 651 the final assignments of individuals to groups obtained with fastStructure revealed that the 652 same genetic groups could be recovered.

653 Figure S2: Maximum-likelihood tree of genetic relationships among populations. Branch 654 lengths are proportional to drift in allele frequencies between populations. The scale with the 655 standard error (s.e.) was extracted from the sample covariance matrix. The red arrow shows 656 a migration event resulting in admixture that passed the significance threshold of the three- 657 population test (f3).

658 Figure S3: Relative sequencing depth measured for genes involved in maltose, iso-maltose 659 and sucrose assimilation. Data were obtained for strains selected in the ”Mixed origin” clade 660 (49 controls and 35 bakery yeasts) and “Mosaic region 3” clade (79 controls and 18 bakery 661 yeasts). A, maltose genes cluster MAL1-3; B, maltose genes cluster MAL3-3; C, iso-maltases 662 genes IMA1-5 and D, invertase gene SUC2.

663 Figure S4: Population size variation after 27h of fermentation in a sourdough synthetic 664 medium among sourdough, commercial and non-bakery strains (other). bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

665 Table

666 Table 1: Ploidy variation in studied strains as revealed by fow cytometry and microsatellite 667 typing origin ploidy total 2n 4n aneuploid commercial 5 21 5 31 sourdough 94 70 34 198 total 99 91 39 229

668 Table 2: Ploidy variation in sourdough strains isolated from France, Italy and Belgium, as 669 revealed by both flow cytometry and microsatellite typing origin ploidy total 2n 4n aneuploid France 66 37 26 129 Italy 18 24 7 49 Belgium 10 9 1 20 total 94 70 34 198 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 1

1.2

1.1

1.0

0.9

0.8 w, relative fitness (4n vs 2n) relative w, 0.7 B32_1 GFP vs QE1 B16_4 GFP vs SBD SBE vs B9b_10 GFP QE2 vs B10L − 1 GFP B16_4 GFP vs B25_1p CLIB_215 GFP vs AE1 MTF4554 vs 6464 GFP MTF3642 vs 6464 GFP MTF1616 vs B10L − 1 GFP CLIB_215 GFP vs MTF3809 MUCL51221 vs B9b_10 GFP Couple of strains (4n vs 2n) bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 2

A B ● 35 10 ● (g) Ploidie ● ● Ploidie 2 30 8 2n (h) ● 2n 25 6 1g 4n t 4n 20 4

max CO ● 15 AE1 AE1 SBE QE1 QE2 SBE QE1 QE2 SBD SBD B25_1p B25_1p MTF4554 MTF1616 MTF3809 MTF3642 MTF4554 MTF1616 MTF3642 MTF3809 CLIB_646 CLIB_646 6464 GFP 6464 GFP B32_1 GFP B16_4 GFP B16_4 GFP B32_1 GFP MUCL51221 MUCL51221 B9b_10 GFP B9b_10 GFP B10L − 1 GFP B10L − 1 GFP CLIB_215 GFP CLIB_215 GFP Strains Strains C D 27 ● ● 3.5 Ploidie 24 Ploidie 3.0 (h) 2n 21 ● 2n 2.5 Vmax

4n t 18 4n 2.0 Vmax (g/L/h) 15 AE1 AE1 SBE QE1 QE2 QE2 SBE QE1 SBD SBD B25_1p B25_1p MTF3809 MTF4554 MTF3809 MTF4554 MTF1616 MTF3642 MTF3642 MTF1616 CLIB_646 CLIB_646 6464 GFP 6464 GFP B32_1 GFP B16_4 GFP B32_1 GFP B16_4 GFP MUCL51221 MUCL51221 B9b_10 GFP B9b_10 GFP B10L − 1 GFP B10L − 1 GFP CLIB_215 GFP CLIB_215 GFP Strains Strains bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Figure 3

1.0

0.8

0.6 0.4 4 0.2

0.0 1.0

0.8

0.6 0.4 5 0.2

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0.6 0.4 6 0.2

0.0 7777777777777777 7979797979797979 IE1IE1IE1IE1IE1IE1IE1IE1 LE3LE3LE3LE3LE3LE3LE3LE3 YA3YA3YA3YA3YA3YA3YA3YA3 NF1NF1NF1NF1NF1NF1NF1NF1 YS2YS2YS2YS2YS2YS2YS2YS2 YS9YS9YS9YS9YS9YS9YS9YS9 AE1AE1AE1AE1AE1AE1AE1AE1 YS4YS4YS4YS4YS4YS4YS4YS4 YQ5YQ5YQ5YQ5YQ5YQ5YQ5YQ5 QE1QE1QE1QE1QE1QE1QE1QE1 SBDSBDSBDSBDSBDSBDSBDSBD 64646464646464646464646464646464 YS20YS20YS20YS20YS20YS20YS20YS20 YS15YS15YS15YS15YS15YS15YS15YS15 YS19YS19YS19YS19YS19YS19YS19YS19 − 1 − 1B9c − 1B9c − 1B9c − 1B9c − 1B9c − 1B9c B9c − 1B9c B29_1B29_1B29_1B29_1B29_1B29_1B29_1B29_1 B32_1B32_1B32_1B32_1B32_1B32_1B32_1B32_1 B16_4B16_4B16_4B16_4B16_4B16_4B16_4B16_4 − 1 − 1B9b − 1B9b − 1B9b − 1B9b − 1B9b − 1B9b − 1 B9b − 1B9b − 1B10 − 1B10 − 1B10 − 1B10 − 1B10 − 1B10 B10 − 1B10 − 15 − 15SD − 15SD − 15SD − 15SD − 15SD − 15SD SD − 15SD YS8(E)YS8(E)YS8(E)YS8(E)YS8(E)YS8(E)YS8(E)YS8(E) YS5(E)YS5(E)YS5(E)YS5(E)YS5(E)YS5(E)YS5(E)YS5(E) Aline20Aline20Aline20Aline20Aline20Aline20Aline20Aline20 − 3B − 3B646 − 3B646 − 3B646 − 3B646 − 3B646 − 3B646 646 − 3B646 − 5C − 5C319 − 5C319 − 5C319 − 5C319 − 5C319 − 5C319 319 − 5C319 − 6C − 6C324 − 6C324 − 6C324 − 6C324 − 6C324 − 6C324 324 − 6C324 B25_1PB25_1PB25_1PB25_1PB25_1PB25_1PB25_1PB25_1P YS10(E)YS10(E)YS10(E)YS10(E)YS10(E)YS10(E)YS10(E)YS10(E) YS11(E)YS11(E)YS11(E)YS11(E)YS11(E)YS11(E)YS11(E)YS11(E) YS22(E)YS22(E)YS22(E)YS22(E)YS22(E)YS22(E)YS22(E)YS22(E) − 1C − 1CSBE − 1CSBE − 1CSBE − 1CSBE − 1CSBE − 1CSBE SBE − 1CSBE CLIB889CLIB889CLIB889CLIB889CLIB889CLIB889CLIB889CLIB889 CLIB340CLIB340CLIB340CLIB340CLIB340CLIB340CLIB340CLIB340 CLIB215CLIB215CLIB215CLIB215CLIB215CLIB215CLIB215CLIB215 Red_StarRed_StarRed_StarRed_StarRed_StarRed_StarRed_StarRed_Star CBS1254CBS1254CBS1254CBS1254CBS1254CBS1254CBS1254CBS1254 CBS1252CBS1252CBS1252CBS1252CBS1252CBS1252CBS1252CBS1252 CBS1387CBS1387CBS1387CBS1387CBS1387CBS1387CBS1387CBS1387 CBS1428CBS1428CBS1428CBS1428CBS1428CBS1428CBS1428CBS1428 CBS1385CBS1385CBS1385CBS1385CBS1385CBS1385CBS1385CBS1385 CLIB208_1 CLIB274_1 CLIB326_1 CLIB318_1 CLIB324_2 CLIB324_2 N34:2 − 4(a) Bruggeman CBS1236 − a CLIB192_1b N134:7 − 1(a) MUCL51209 MUCL30387 MUCL30388 MUCL51223 MUCL51215 MUCL51226 MUCL52906 MUCL51236 MUCL52901 MUCL42920 Fleischmann CLIB215_3B DBVPG1058 N26 − 1 10:7 5(a) P1 P2 P3 P4 P5 P6 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Figu re 4

Microsatel lite

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P5 P6 Tree scale : 0.1

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Phylogenetic tree obtained from 33032 biallelic SNPs (mind:0.5, geno:0.1, maf:0.03, ld:0.5) from 68 bakery strains using RAxML (evolution model GTRGAMMA). The most likely tree from 100 boost rap replicates was presented. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 5

Population P1

P2

P3

P4

P5 Wine/European Mosaic region 1 P6

African beer Isolation

Commercial Sourdough

Mixed origin

Asian fermentation

Mosaic region 3

Tree scale: 0.1 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 6

K = 15

1011 genomes

clades 8.Mixed origin 8.Mixed origin 8. Mixed Ecuadorean 21. 6. African beer 6. African 25. Sake 26. Asian fermentation 26. Asian 3. Brazilian bioethanol 3. Brazilian

7. Mosaic beer 7. Mosaic M3. Mosaic region 3 region Mosaic M3. M3. Mosaic region 3 region Mosaic M3. 1. Wine/European 18. Far east asia east 18. Far 11. Ale beer 11. Ale 1. Wine/European 1

0.8

0.6

0.4

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Baker yeast clusters P6 P1 P2 P3 P4 P5

Baker yeasts Commercial Sourdough bioRxiv preprint doi: https://doi.org/10.1101/2020.05.28.120584; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Figure 7

CO2max t1g

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Figu re 8 Tree scale : 0.1

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MUCL52906 B9c 8 MUCL51208

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B9c 12 B10L-17

B10L-16 B9c 13 B10L-29 B9c 11 B10L-30 Al39 B10L-36 B10L-21

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