Humans have exploited the budding yeast, Saccharomyces cerevisiae, for over ten thousand years for brewing and baking. This close connection with human activity led Louis Pasteur to discover its essential role in alcoholic fermentation in 1857 (Pasteur, 1858). Brewing was also the key motivation for the start of yeast genetics. The initial breeding experiments by Ojvind Winge at the Carlsberg laboratory in the 1930s aimed to combine desirable brewing traits by crossing different strains (Barnett, 2007). Our ability to control and manipulate its life cycle has made the budding yeast the most powerful, single-cell eukaryotic system for biological research, and it was rapidly adopted around the world to investigate virtually every aspect of biology. Early on in S. cerevisiae research, the scientific community adopted a single reference isolate, the S288c strain, or strains derived from it. This reference strain was obtained by crossing several parental strains and has the peculiar trait that it can be maintained with a stable haploid background, making it easier to study the effects of mutations (Mortimer and Johnston, 1986). In 1996, S288c became the first eukaryotic organism to have its genome completely sequenced (Goffeau et al., 1996), and strain libraries were subsequently developed for it, such as libraries of deletion (Giaever et al., 2002) and overexpression mutants (Sopko et al., 2006), and strains with genes tagged by reporter genes (Huh et al., 2003). These libraries allow researchers to investigate the functional biology of every S. cerevisiae gene. The availability of such a powerful functional genomics toolkit has facilitated some remarkable discoveries, such as defining the yeast genetic and protein interaction networks (Botstein and Fink, 2011).

However, this reference strain provides very little information about the natural history of this species, and its combinations of alleles have never been exposed to selection in a natural setting. This strain is also an outlier in terms of its phenotypic properties (Warringer et al., 2011), and the presence of auxotrophic markers (i.e., mutations that render a yeast cell unable to synthesize an essential compound) in its genome has serious consequences for many traits (Mülleder et al., 2012). In the past decade, we have witnessed a renewed interest in understanding the fascinating secret life of the budding yeast. On-going studies of thousands of isolates, both wild and those associated with human activities, will reveal the impact humans have had on the evolution of this species and will help to keep S. cerevisiae at the forefront of systems genetics.

The S. cerevisiae lifecycle, under precisely controlled laboratory conditions, is one of the best understood at the mechanistic level. Our ability to control its sexual cycle and to switch it between mitotic and meiotic reproduction is one of the great experimental strengths of this yeast system. Paradoxically, we know very little about its life cycle in natural settings (Box 1), and what little we do know is indirectly inferred from studying its life cycle in the lab, which precludes any firm conclusions (Boynton and Greig, 2014). In the wild, yeast cells are found in fluctuating environments and are often subjected to a shortage of food. For instance, one of this yeast's natural habitats, oak bark, subjects it to seasonal cycles of tree sap flow, in addition to changing climate conditions. S. cerevisiae cells therefore likely spend much of their time in a non-dividing state called quiescence (Gray et al., 2004). When conditions become favourable, S. cerevisiae is able to grow on a modest array of fermentable and non-fermentable carbon sources (mostly six-carbon sugars). The availability of nutrients is likely to result in a rapid, mitotic clonal expansion of diploid yeast cells (Figure 1A,C).

Figure 1

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Sexual cycles can be triggered by environmental cues, such as nutrient depletion, and result in the production of four meiotic spores that have two distinct mating types (a and α), analogous to human eggs and sperms (Figure 1B). Meiotic spores tested in laboratory experiments are highly resistant to various stresses, such as high and low temperature and desiccation, and it is reasonable to assume that in a wild habitat they can persist for long periods of time until favourable, nutrient-rich conditions allow germination. Haploid spores eventually re-establish diploid lines, either by mating with their own mitotic daughter cells after switching mating type (haplo-selfing), by mating with another spore created by the same meiotic event (intra-tetrad mating) or, more rarely, by mating with an unrelated individual (outcrossing) (Knop, 2006). These different mating solutions should have very different effects on species evolution and population structure. However, due to the microscopic size of yeast, the relative frequency of different modes of reproduction in the wild can only be inferred retrospectively by genome analysis (Ruderfer et al., 2006; Tsai et al., 2008). Population genomic studies indicate that budding yeast mostly reproduces asexually and that outcrossing is rare. Experiments have shown that outbreeding can be promoted by another popular model organism, the fruit fly D. melanogaster, which is attracted to and consumes yeast cells living on fruit in the wild and thereby acts as a vector, aiding their geographical dispersal (Reuter et al., 2007; Buser et al., 2014; Christiaens et al., 2014). Furthermore, outcrossing is not restricted to mating within the species; introgressed genomic regions and interspecies hybrids with other closely related species are frequently observed (Liti et al., 2006; Novo et al., 2009). S. cerevisiae belong to a group of species named the Saccharomyces sensu stricto complex, which can generate viable hybrids when interbred (Liti and Louis, 2005; Replansky et al., 2008; Hittinger, 2013; Borneman and Pretorius, 2015). One fortunate example of this is the hybridization between S. cerevisiae and S. eubayanus, which led to the hybrid species S. pastorianus, used worldwide in the brewing industry to produce lager (Libkind et al., 2011).

The abundance of S. cerevisiae associated with fermented beverages initially gave rise to the notion of a ‘man-made organism’, restricted to human settings (Vaughan-Martini and Martini, 1995). The chemical composition of the fermentation environment can vary between different types of beverage, and also throughout the fermentation process. This substrate variability has selected for different yeast breeds that are optimised to ferment specific products, such as wine and sake (Fay and Benavides, 2005). Additionally, several genome signatures of human-driven adaptation have been reported (Sicard and Legras, 2011). However, all fermented beverages adhere to the basic rules of alcoholic fermentation, with different types of sugars being rapidly transformed into ethanol. This metabolic trait has independently evolved in yeasts multiple times, perhaps as an adaptive strategy either because producing high concentrations of ethanol can help to outcompete other microorganisms (Rozpędowska et al., 2011; Thompson et al., 2013) or because it can support faster growth than aerobic fermentation (Pfeiffer et al., 2001). The alcoholic fermentation of sugar-rich substrates by S. cerevisiae and by other yeast species is not exclusive to human beverages. Ethanol content almost equivalent to that of lager beer has been detected in the spontaneously fermenting nectar of the bertam palm in the Malaysian rainforests, although it has not been determined if S. cerevisiae is the dominant fermenter in this context (Figure 2A). This alcoholic nectar is heavily consumed by the pen-tailed treeshrew (Wiens et al., 2008).

Figure 2

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Apart from the human-associated environments of breweries and bakeries, another set of S. cerevisiae strains has an even more intimate association with humans. These include pathogenic strains isolated from immunocompromised patients and strains associated with Candida infections (Muller et al., 2011). Clinically relevant strains of S. cerevisiae can grow at high temperatures (above 40°C), perhaps as a result of adaptation to human body niches. A surprising case of non-pathogenic human colonization was recently reported from an Amerindian community living in a remote area of French Guiana. In this cohort, S. cerevisiae is frequently isolated from stools, in contrast to industrialised countries where Candida albicans is predominant (Angebault et al., 2013). This finding adds to a growing list of S. cerevisiae detected in the human microbiota of both healthy and sick individuals (Rizzetto et al., 2014). Colonizers are likely derived from food and beverages and appear to be able to persist in the human gut environment. Such resistance to the human gut is also observed in a variant of S. cerevisiae, known as S. boulardii, which is marketed as a probiotic.

In addition to human-related environments, S. cerevisiae has also been isolated from wild habitats. This is not a trivial task given the small population size present in nutrient-poor substrates. The sampling approach used relies on an enrichment medium that favours the growth of S. cerevisiae over other microbes that coexist in the sample. Oak trees (Quercus spp., Fagaceae family) represent a natural niche where S. cerevisiae, together with closely related species of the sensu stricto complex, has frequently been sampled across different continents (Sniegowski et al., 2002; Sampaio and Gonçalves, 2008). Additional niches include other trees belonging to the Fagaceae family (such as beech and chestnut), other plants with completely different geographic ranges (e.g., cactuses), and associated soil and insects (Liti et al., 2009; Stefanini et al., 2012; Naumov et al., 2013). Perhaps the most successful field survey has been carried out across China (Wang et al., 2012). This study revealed for the first time that S. cerevisiae has a rather ubiquitous distribution, one that is not limited to human-associated environments but extends into other habitats, such as primary forests that are remote from human activity (Figure 2B). These new studies are challenging our concept of the natural niches of this yeast, by showing that its history goes far beyond its association with humans. Additional systematic field surveys will help to further refine our knowledge of its complex ecology (Box 1).

Population genomics has provided a powerful means by which to illuminate the evolutionary history of budding yeast. In initial genome sequencing studies, half of the S. cerevisiae strains sequenced fell into a number of distinct lineages (Figure 3A). Genetic variants within these lineages are mostly unique to a subpopulation and absent in others and evenly distributed across the genome (Liti et al., 2009). Variation in phenotype tends to follow population structure (Warringer et al., 2011). Some of these lineages are characteristic of distinct fermentation processes and might represent examples of domesticated breeds (Fay and Benavides, 2005; Schacherer et al., 2009). These strains do not strictly follow geographic boundaries, for example, wine strains from Europe, Australia, Chile and New Zealand share recent ancestry and reflect human migration history (Legras et al., 2007; Liti et al., 2009; Goddard et al., 2010; Dunn et al., 2012).

Figure 3

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Other lineages are not associated with human activity and appear to be characteristic of the geographic area. These include oak strains from woodlands in North America and bertam palm strains from the Malaysian rainforest. The Malaysian lineage has the peculiarity of being reproductively isolated from all other lineages due to a complex series of chromosomal rearrangements (Cubillos et al., 2011; Marie-Nelly et al., 2014).

Although full genome information is not yet available for Chinese isolates of S. cerevisiae, they appear to exhibit strong population structure, with essentially double the combined amount of genetic variation identified in S. cerevisiae isolates sampled from the rest of the world (Wang et al., 2012). Chinese isolates from primeval forests fall into ancient and remarkably diverged lineages (Figure 3A). These results suggest that China harbours a reservoir of S. cerevisiae natural genetic variation, which perhaps gives an indication as to where the species originated. This enrichment of genetic diversity is not limited to S. cerevisiae intra-species variation as Far East Asia is also the only region where all the Saccharomyces sensu stricto species have been isolated.

In addition to these distinct lineages, many S. cerevisiae strains have been found, after sequencing, to have mosaic recombinant genomes, which reflect a mixed ancestry likely originating from outcrosses between genetically distinct lineages (Figure 3B). Mosaic strains have probably arisen as result of human activities (Liti et al., 2009). Clinical isolates and those used in bakeries and in the laboratory tend to be mosaics, and most of their genomes can be traced to already characterized genetically distinct lineages. Future population genomics studies should further define the genomic features of S. cerevisiae and allow the hybridisation events that generated these mosaic strains to be reconstructed.

Recent insights into the natural history of S. cerevisiae have shown that the reference lab strains represent only a subset of the many aspects of natural yeast life. Population genomics offer a powerful approach, termed ‘reverse ecology’ (Li et al., 2008), to investigate the natural history of the species. Population-level sequencing applied to thousands of strains will further illuminate the natural history of S. cerevisiae, and the genomes of highly diverged lineages that predate domestication will reveal the impact of human activity on the species. Analysing large numbers of strains also offers the opportunity to directly test associations between genotype and phenotype. Some lineages have specific genomic signatures that underlie phenotypes (Skelly et al., 2013) but whether this is driven by adaptation or by genetic drift remains an open question (Warringer et al., 2011). Genotype-phenotype associations are not restricted to single nucleotide polymorphisms (SNPs) but can extend to genome content, copy number, ploidy and structural variation (Box 1). Recent reports have shown that accessory genes vary between lineages and constitute a large fraction of genome variation between individuals (Bergström et al., 2014). Certain forms of non-genetic variation, such as prions, might also be important determinants of phenotypic variation (Jarosz et al., 2014). The legacy from classical genetics also offers possibilities to develop new tools and methodologies. Artificial populations of recombinant strains are now available, including a multi-parent population derived from highly diverged lineages (Cubillos et al., 2013). These approaches promise to bring yeast to the forefront of complex trait analysis together with other model systems where multi-parent populations are already established (Kover et al., 2009; Aylor et al., 2011; King et al., 2012).

In summary, a better knowledge of the natural history of this species is essential for interpreting its biology. Identifying how the S. cerevisiae life cycle progresses in the wild will allow us to better understand the genetic and environmental factors that are relevant to its fitness (Box 1). Yeast fitness has been largely approximated to mitotic growth, which disregards mortality during periods that do not support reproduction. However, it is likely that yeasts in nature spend most of their chronological life in a non-dividing state. The ability to survive in that state is therefore probably exposed to strong selection. Thus, measuring the impact of natural genetic variation on longevity related traits might be crucial for understanding the selective pressures that yeasts are exposed to during their life cycle. Consideration must also be given to other aspects of the life cycle, such as sporulation, spore viability and germination time, each of which are also complex traits and strongly affected by the environment. Exploiting the natural variation of S. cerevisiae and its close relatives using genomics methodologies is enabling a new era of functional and evolutionary genetics studies of this classic model organism (Nieduszynski and Liti, 2011; Fay, 2013; Lehner, 2013).

1. 1. Angebault C
   2. Djossou F
   3. Abélanet S
   4. Permal E
   5. Ben Soltana M
   6. Diancourt L
   7. Bouchier C
   8. Woerther P-L
   9. Catzeflis F
   10. Andremont A
   11. d'Enfert C
   12. Bougnoux ME

   (2013) Candida albicans is not always the preferential yeast colonizing humans: a study in Wayampi Amerindians

   Journal of Infectious Diseases 208:1705–1716.

   https://doi.org/10.1093/infdis/jit389

   • Google Scholar
2. 1. Aylor DL
   2. Valdar W
   3. Foulds-Mathes W
   4. Buus RJ
   5. Verdugo RA
   6. Baric RS
   7. Ferris MT
   8. Frelinger JA
   9. Heise M
   10. Frieman MB
   11. Gralinski LE
   12. Bell TA
   13. Didion JD
   14. Hua K
   15. Nehrenberg DL
   16. Powell CL
   17. Steigerwalt J
   18. Xie Y
   19. Kelada SN
   20. Collins FS
   21. Yang IV
   22. Schwartz DA
   23. Branstetter LA
   24. Chesler EJ
   25. Miller DR
   26. Spence J
   27. Liu EY
   28. McMillan L
   29. Sarkar A
   30. Wang J
   31. Wang W
   32. Zhang Q
   33. Broman KW
   34. Korstanje R
   35. Durrant C
   36. Mott R
   37. Iraqi FA
   38. Pomp D
   39. Threadgill D
   40. de Villena FP
   41. Churchill GA

   (2011) Genetic analysis of complex traits in the emerging Collaborative Cross

   Genome Research 21:1213–1222.

   https://doi.org/10.1101/gr.111310.110

   • Google Scholar
3. 1. Barnett JA

   (2007) A history of research on yeasts 10: foundations of yeast genetics

   Yeast 24:799–845.

   https://doi.org/10.1002/yea.1513

   • Google Scholar
4. 1. Bergström A
   2. Simpson JT
   3. Salinas F
   4. Barré B
   5. Parts L
   6. Zia A
   7. Nguyen Ba AN
   8. Moses AM
   9. Louis EJ
   10. Mustonen V
   11. Warringer J
   12. Durbin R
   13. Liti G

   (2014) A high-definition view of functional genetic variation from natural yeast genomes

   Molecular Biology and Evolution 31:872–888.

   https://doi.org/10.1093/molbev/msu037

   • Google Scholar
5. 1. Borneman AR
   2. Pretorius IS

   (2015) Genomic Insights into the Saccharomyces sensu stricto Complex

   Genetics 199:281–291.

   https://doi.org/10.1534/genetics.114.173633

   • Google Scholar
6. 1. Botstein D
   2. Fink GR

   (2011) Yeast: an experimental organism for 21st Century biology

   Genetics 189:695–704.

   https://doi.org/10.1534/genetics.111.130765

   • Google Scholar
7. 1. Boynton PJ
   2. Greig D

   (2014) The ecology and evolution of non-domesticated Saccharomyces species

   Yeast 31:449–462.

   https://doi.org/10.1002/yea.3040

   • Google Scholar
8. 1. Buser CC
   2. Newcomb RD
   3. Gaskett AC
   4. Goddard MR

   (2014) Niche construction initiates the evolution of mutualistic interactions

   Ecology Letters 17:1257–1264.

   https://doi.org/10.1111/ele.12331

   • Google Scholar
9. 1. Christiaens JF
   2. Franco LM
   3. Cools TL
   4. De Meester L
   5. Michiels J
   6. Wenseleers T
   7. Hassan BA
   8. Yaksi E
   9. Verstrepen KJ

   (2014) The fungal Aroma gene ATF1 Promotes dispersal of yeast cells through insect vectors

   Cell Reports 9:425–432.

   https://doi.org/10.1016/j.celrep.2014.09.009

   • Google Scholar
10. 1. Cubillos FA
    2. Billi E
    3. Zörgö E
    4. Parts L
    5. Fargier P
    6. Omholt S
    7. Blomberg A
    8. Warringer J
    9. Louis EJ
    10. Liti G

    (2011) Assessing the complex architecture of polygenic traits in diverged yeast populations

    Molecular Ecology 20:1401–1413.

    https://doi.org/10.1111/j.1365-294X.2011.05005.x

    • Google Scholar
11. 1. Cubillos FA
    2. Parts L
    3. Salinas F
    4. Bergström A
    5. Zia A
    6. Mustonen V
    7. Warringer J
    8. Louis EJ
    9. Durbin R
    10. Liti G

    (2013) High-resolution mapping of complex traits with a four-parent advanced intercross yeast population

    Genetics 195:1141–1155.

    https://doi.org/10.1534/genetics.113.155515

    • Google Scholar
12. 1. Dunn B
    2. Richter C
    3. Kvitek DJ
    4. Pugh T
    5. 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 Research 22:908–924.

    https://doi.org/10.1101/gr.130310.111

    • Google Scholar
13. 1. Fay JC
    2. Benavides JA

    (2005) Evidence for domesticated and wild populations of Saccharomyces cerevisiae

    PLOS Genetics 1:66–71.

    https://doi.org/10.1371/journal.pgen.0010005

    • Google Scholar
14. 1. Fay JC

    (2013) The molecular basis of phenotypic variation in yeast

    Current Opinion in Genetics & Development 23:672–677.

    https://doi.org/10.1016/j.gde.2013.10.005

    • Google Scholar
15. 1. Gerke JP
    2. Chen CTL
    3. Cohen BA

    (2006) Natural isolates of Saccharomyces cerevisiae display complex genetic variation in sporulation efficiency

    Genetics 174:985–997.

    https://doi.org/10.1534/genetics.106.058453

    • Google Scholar
16. 1. Giaever G
    2. Chu AM
    3. Ni L
    4. Connelly C
    5. Riles L
    6. Véronneau S
    7. Dow S
    8. Lucau-Danila A
    9. Anderson K
    10. André B
    11. Arkin AP
    12. Astromoff A
    13. El-Bakkoury M
    14. Bangham R
    15. Benito R
    16. Brachat S
    17. Campanaro S
    18. Curtiss M
    19. Davis K
    20. Deutschbauer A
    21. Entian KD
    22. Flaherty P
    23. Foury F
    24. Garfinkel DJ
    25. Gerstein M
    26. Gotte D
    27. Güldener U
    28. Hegemann JH
    29. Hempel S
    30. Herman Z
    31. Jaramillo DF
    32. Kelly DE
    33. Kelly SL
    34. Kötter P
    35. LaBonte D
    36. Lamb DC
    37. Lan N
    38. Liang H
    39. Liao H
    40. Liu L
    41. Luo C
    42. Lussier M
    43. Mao R
    44. Menard P
    45. Ooi SL
    46. Revuelta JL
    47. Roberts CJ
    48. Rose M
    49. Ross-Macdonald P
    50. Scherens B
    51. Schimmack G
    52. Shafer B
    53. Shoemaker DD
    54. Sookhai-Mahadeo S
    55. Storms RK
    56. Strathern JN
    57. Valle G
    58. Voet M
    59. Volckaert G
    60. Wang CY
    61. Ward TR
    62. Wilhelmy J
    63. Winzeler EA
    64. Yang Y
    65. Yen G
    66. Youngman E
    67. Yu K
    68. Bussey H
    69. Boeke JD
    70. Snyder M
    71. Philippsen P
    72. Davis RW
    73. Johnston M

    (2002) Functional profiling of the Saccharomyces cerevisiae genome

    Nature 418:387–391.

    https://doi.org/10.1038/nature00935

    • Google Scholar
17. 1. Goddard MR
    2. Anfang N
    3. Tang R
    4. Gardner RC
    5. Jun C

    (2010) A distinct population of Saccharomyces cerevisiae in New Zealand: evidence for local dispersal by insects and human-aided global dispersal in oak barrels

    Environmental Microbiology 12:63–73.

    https://doi.org/10.1111/j.1462-2920.2009.02035.x

    • Google Scholar
18. 1. Goffeau A
    2. Barrell BG
    3. Bussey H
    4. Davis RW
    5. Dujon B
    6. Feldmann H
    7. Galibert F
    8. Hoheisel JD
    9. Jacq C
    10. Johnston M
    11. Louis EJ
    12. Mewes HW
    13. Murakami Y
    14. Philippsen P
    15. Tettelin H
    16. Oliver SG

    (1996) Life with 6000 genes

    Science 274:546–563–7.

    https://doi.org/10.1126/science.274.5287.546

    • Google Scholar
19. 1. Gray JV
    2. Petsko GA
    3. Johnston GC
    4. Ringe D
    5. Singer RA
    6. Werner-Washburne M

    (2004) ‘Sleeping beauty’: quiescence in Saccharomyces cerevisiae

    Microbiology and Molecular Biology Reviews 68:187–206.

    https://doi.org/10.1128/MMBR.68.2.187-206.2004

    • Google Scholar
20. 1. Hittinger CT

    (2013) Saccharomyces diversity and evolution: a budding model genus

    Trends in Genetics 29:309–317.

    https://doi.org/10.1016/j.tig.2013.01.002

    • Google Scholar
21. 1. Huh WK
    2. Falvo JV
    3. Gerke LC
    4. Carroll AS
    5. Howson RW
    6. Weissman JS
    7. O'Shea EK

    (2003) Global analysis of protein localization in budding yeast

    Nature 425:686–691.

    https://doi.org/10.1038/nature02026

    • Google Scholar
22. 1. Jarosz DF
    2. Brown JCS
    3. Walker GA
    4. Datta MS
    5. Ung WL
    6. Lancaster AK
    7. Rotem A
    8. Chang A
    9. Newby GA
    10. Weitz DA
    11. Bisson LF
    12. Lindquist S

    (2014) Cross-kingdom chemical communication drives a heritable, mutually beneficial prion-based transformation of metabolism

    Cell 158:1083–1093.

    https://doi.org/10.1016/j.cell.2014.07.025

    • Google Scholar
23. 1. King EG
    2. Merkes CM
    3. McNeil CL
    4. Hoofer SR
    5. Sen S
    6. Broman KW
    7. Long AD
    8. Macdonald SJ

    (2012) Genetic dissection of a model complex trait using the Drosophila synthetic population resource

    Genome Research 22:1558–1566.

    https://doi.org/10.1101/gr.134031.111

    • Google Scholar
24. 1. Knop M

    (2006) Evolution of the hemiascomycete yeasts: on life styles and the importance of inbreeding

    Bioessays 28:696–708.

    https://doi.org/10.1002/bies.20435

    • Google Scholar
25. 1. Kover PX
    2. Valdar W
    3. Trakalo J
    4. Scarcelli N
    5. Ehrenreich IM
    6. Purugganan MD
    7. Durrant C
    8. Mott R

    (2009) A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana

    PLOS Genetics 5:e1000551.

    https://doi.org/10.1371/journal.pgen.1000551

    • Google Scholar
26. 1. Legras J-L
    2. Merdinoglu D
    3. Cornuet JM
    4. Karst F

    (2007) Bread, beer and wine: Saccharomyces cerevisiae diversity reflects human history

    Molecular Ecology 16:2091–2102.

    https://doi.org/10.1111/j.1365-294X.2007.03266.x

    • Google Scholar
27. 1. Lehner B

    (2013) Genotype to phenotype: lessons from model organisms for human genetics

    Nature Reviews Genetics 14:168–178.

    https://doi.org/10.1038/nrg3404

    • Google Scholar
28. 1. Li YF
    2. Costello JC
    3. Holloway AK
    4. Hahn MW

    (2008) ‘Reverse ecology’ and the power of population genomics

    Evolution 62:2984–2994.

    https://doi.org/10.1111/j.1558-5646.2008.00486.x

    • Google Scholar
29. 1. Libkind D
    2. Hittinger CT
    3. Valério E
    4. Gonçalves C
    5. Dover J
    6. Johnston M
    7. Gonçalves P
    8. Sampaio JP

    (2011) Microbe domestication and the identification of the wild genetic stock of lager-brewing yeast

    Proceedings of the National Academy of Sciences of USA 108:14539–14544.

    https://doi.org/10.1073/pnas.1105430108

    • Google Scholar
30. 1. Liti G
    2. Louis EJ

    (2005) Yeast evolution and comparative genomics

    Annual Review of Microbiology 59:135–153.

    https://doi.org/10.1146/annurev.micro.59.030804.121400

    • Google Scholar
31. 1. Liti G
    2. Barton DBH
    3. Louis EJ

    (2006)

    Sequence diversity, reproductive isolation and species concepts in Saccharomyces

    Genetics 174:839–850.

    • Google Scholar
32. 1. Liti G
    2. Carter DM
    3. Moses AM
    4. Warringer J
    5. Parts L
    6. James SA
    7. Davey RP
    8. Roberts IN
    9. Burt A
    10. Koufopanou V
    11. Tsai IJ
    12. Bergman CM
    13. Bensasson D
    14. O'Kelly MJ
    15. van Oudenaarden A
    16. Barton DB
    17. Bailes E
    18. Nguyen AN
    19. Jones M
    20. Quail MA
    21. Goodhead I
    22. Sims S
    23. Smith F
    24. Blomberg A
    25. Durbin R
    26. Louis EJ

    (2009) Population genomics of domestic and wild yeasts

    Nature 458:337–341.

    https://doi.org/10.1038/nature07743

    • Google Scholar
33. 1. Marie-Nelly H
    2. Marbouty M
    3. Cournac A
    4. Flot J-F
    5. Liti G
    6. Parodi DP
    7. Syan S
    8. Guillén N
    9. Margeot A
    10. Zimmer C
    11. Koszul R

    (2014) High-quality genome (re)assembly using chromosomal contact data

    Nature Communications 5:5695.

    https://doi.org/10.1038/ncomms6695

    • Google Scholar
34. 1. Mortimer RK
    2. Johnston JR

    (1986)

    Genealogy of principal strains of the yeast genetic stock center

    Genetics 113:35–43.

    • Google Scholar
35. 1. Mülleder M
    2. Capuano F
    3. Pir P
    4. Christen S
    5. Sauer U
    6. Oliver SG
    7. Ralser M

    (2012) A prototrophic deletion mutant collection for yeast metabolomics and systems biology

    Nature Biotechnology 30:1176–1178.

    https://doi.org/10.1038/nbt.2442

    • Google Scholar
36. 1. Muller LA
    2. Lucas JE
    3. Georgianna DR
    4. McCusker JH

    (2011) Genome-wide association analysis of clinical vs. nonclinical origin provides insights into Saccharomyces cerevisiae pathogenesis

    Molecular Ecology 20:4085–4097.

    https://doi.org/10.1111/j.1365-294X.2011.05225.x

    • Google Scholar
37. 1. Naumov GI
    2. Lee C-F
    3. Naumova ES

    (2013) Molecular genetic diversity of the Saccharomyces yeasts in Taiwan: Saccharomyces arboricola, Saccharomyces cerevisiae and Saccharomyces kudriavzevii

    Antonie Van Leeuwenhoek 103:217–228.

    https://doi.org/10.1007/s10482-012-9803-2

    • Google Scholar
38. 1. Nieduszynski CA
    2. Liti G

    (2011) From sequence to function: Insights from natural variation in budding yeasts

    Biochimica Et Biophysica Acta 1810:959–966.

    https://doi.org/10.1016/j.bbagen.2011.02.004

    • Google Scholar
39. 1. Novo M
    2. Bigey F
    3. Beyne E
    4. Galeote V
    5. Gavory F
    6. Mallet S
    7. Cambon B
    8. Legras J-L
    9. Wincker P
    10. Casaregola S
    11. Dequin S

    (2009) Eukaryote-to-eukaryote gene transfer events revealed by the genome sequence of the wine yeast Saccharomyces cerevisiae EC1118

    Proceedings of the National Academy of Sciences of USA 106:16333–16338.

    https://doi.org/10.1073/pnas.0904673106

    • Google Scholar
40. 1. Pasteur L

    (1858)

    Nouveaux faits concernant l'histoire de la fermentation alcoolique

    Comptes Rendus Chimie 47:1011–1013.

    • Google Scholar
41. 1. Pfeiffer T
    2. Schuster S
    3. Bonhoeffer S

    (2001) Cooperation and competition in the evolution of ATP-producing pathways

    Science 292:504–507.

    https://doi.org/10.1126/science.1058079

    • Google Scholar
42. 1. Replansky T
    2. Koufopanou V
    3. Greig D
    4. Bell G

    (2008) Saccharomyces sensu stricto as a model system for evolution and ecology

    Trends in Ecology & Evolution 23:494–501.

    https://doi.org/10.1016/j.tree.2008.05.005

    • Google Scholar
43. 1. Reuter M
    2. Bell G
    3. Greig D

    (2007) Increased outbreeding in yeast in response to dispersal by an insect vector

    Current Biology 17:R81–R83.

    https://doi.org/10.1016/j.cub.2006.11.059

    • Google Scholar
44. 1. Rizzetto L
    2. De Filippo C
    3. Cavalieri D

    (2014) Richness and diversity of mammalian fungal communities shape innate and adaptive immunity in health and disease

    European Journal of Immunology 44:3166–3181.

    https://doi.org/10.1002/eji.201344403

    • Google Scholar
45. 1. Rozpędowska E
    2. Hellborg L
    3. Ishchuk OP
    4. Orhan F
    5. Galafassi S
    6. Merico A
    7. Woolfit M
    8. Compagno C
    9. Piskur J

    (2011) Parallel evolution of the make-accumulate-consume strategy in Saccharomyces and Dekkera yeasts

    Nature Communications 2:302.

    https://doi.org/10.1038/ncomms1305

    • Google Scholar
46. 1. Ruderfer DM
    2. Pratt SC
    3. Seidel HS
    4. Kruglyak L

    (2006) Population genomic analysis of outcrossing and recombination in yeast

    Nature Genetics 38:1077–1081.

    https://doi.org/10.1038/ng1859

    • Google Scholar
47. 1. Sampaio JP
    2. Gonçalves P

    (2008) Natural populations of Saccharomyces kudriavzevii in Portugal are associated with oak bark and are sympatric with S. cerevisiae and S. paradoxus

    Applied and Environmental Microbiology 74:2144–2152.

    https://doi.org/10.1128/AEM.02396-07

    • Google Scholar
48. 1. Schacherer J
    2. Shapiro JA
    3. Ruderfer DM
    4. Kruglyak L

    (2009) Comprehensive polymorphism survey elucidates population structure of Saccharomyces cerevisiae

    Nature 458:342–345.

    https://doi.org/10.1038/nature07670

    • Google Scholar
49. 1. Sicard D
    2. Legras JL

    (2011) Bread, beer and wine: yeast domestication in the Saccharomyces sensu stricto complex

    Comptes Rendus Biologies 334:229–236.

    https://doi.org/10.1016/j.crvi.2010.12.016

    • Google Scholar
50. 1. Skelly DA
    2. Merrihew GE
    3. Riffle M
    4. Connelly CF
    5. Kerr EO
    6. Johansson M
    7. Jaschob D
    8. Graczyk B
    9. Shulman NJ
    10. Wakefield J
    11. Cooper SJ
    12. Fields S
    13. Noble WS
    14. Muller EG
    15. Davis TN
    16. Dunham MJ
    17. Maccoss MJ
    18. Akey JM

    (2013) Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeast

    Genome Research 23:1496–1504.

    https://doi.org/10.1101/gr.155762.113

    • Google Scholar
51. 1. Sniegowski PD
    2. Dombrowski PG
    3. Fingerman E

    (2002)

    Saccharomyces cerevisiae and Saccharomyces paradoxus coexist in a natural woodland site in North America and display different levels of reproductive isolation from European conspecifics

    FEMS Yeast Research 1:299–306.

    • Google Scholar
52. 1. Sopko R
    2. Huang D
    3. Preston N
    4. Chua G
    5. Papp B
    6. Kafadar K
    7. Snyder M
    8. Oliver SG
    9. Cyert M
    10. Hughes TR
    11. Boone C
    12. Andrews B

    (2006) Mapping pathways and phenotypes by systematic gene overexpression

    Molecular Cell 21:319–330.

    https://doi.org/10.1016/j.molcel.2005.12.011

    • Google Scholar
53. 1. Stefanini I
    2. Dapporto L
    3. Legras J-L
    4. Calabretta A
    5. Di Paola M
    6. De Filippo C
    7. Viola R
    8. Capretti P
    9. Polsinelli M
    10. Turillazzi S
    11. Cavalieri D

    (2012) Role of social wasps in Saccharomyces cerevisiae ecology and evolution

    Proceedings of the National Academy of Sciences of USA 109:13398–13403.

    https://doi.org/10.1073/pnas.1208362109

    • Google Scholar
54. 1. Thompson DA
    2. Roy S
    3. Chan M
    4. Styczynsky MP
    5. Pfiffner J
    6. French C
    7. Socha A
    8. Thielke A
    9. Napolitano S
    10. Muller P
    11. Kellis M
    12. Konieczka JH
    13. Wapinski I
    14. Regev A

    (2013) Evolutionary principles of modular gene regulation in yeasts

    eLife 2:e00603.

    https://doi.org/10.7554/eLife.00603

    • Google Scholar
55. 1. Tsai IJ
    2. Bensasson D
    3. Burt A
    4. Koufopanou V

    (2008) Population genomics of the wild yeast Saccharomyces paradoxus: Quantifying the life cycle

    Proceedings of the National Academy of Sciences of USA 105:4957–4962.

    https://doi.org/10.1073/pnas.0707314105

    • Google Scholar
56. 1. Vaughan-Martini A
    2. Martini A

    (1995) Facts, myths and legends on the prime industrial microorganism

    Journal of Industrial Microbiology 14:514–522.

    https://doi.org/10.1007/BF01573967

    • Google Scholar
57. 1. Wang QM
    2. Liu WQ
    3. Liti G
    4. Wang SA
    5. Bai FY

    (2012) Surprisingly diverged populations of Saccharomyces cerevisiae in natural environments remote from human activity

    Molecular Ecology 21:5404–5417.

    https://doi.org/10.1111/j.1365-294X.2012.05732.x

    • Google Scholar
58. 1. Warringer J
    2. Zörgö E
    3. Cubillos FA
    4. Gjuvsland A
    5. Simpson JT
    6. Forsmark A
    7. Durbin R
    8. Omholt SW
    9. Louis EJ
    10. Liti G
    11. Moses A
    12. Blomberg A

    (2011) Trait variation in yeast is defined by population history

    PLOS Genetics 7:e1002111.

    https://doi.org/10.1371/journal.pgen.1002111

    • Google Scholar
59. 1. Wiens F
    2. Zitzmann A
    3. Lachance M-A
    4. Yegles M
    5. Pragst F
    6. Wurst FM
    7. von Holst D
    8. Guan SL
    9. Spanagel R

    (2008) Chronic intake of fermented floral nectar by wild treeshrews

    Proceedings of the National Academy of Sciences of USA 105:10426–10431.

    https://doi.org/10.1073/pnas.0801628105

    • Google Scholar

Author details

1. Gianni Liti

   Institute for Research on Cancer and Ageing of Nice, CNRS UMR 7284, INSERM U1081, University of Nice Sophia Antipolis, Nice, France

   Contribution

   GL, Drafting or revising the article

   For correspondence

   liti.gianni@gmail.com

   Competing interests

   The author declares that no competing interests exist.

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