The effect of spontaneous mutations on CUP1 copy number and copper tolerance in Saccharomyces cerevisiae

The effect of spontaneous mutations on CUP1 copy number and copper tolerance in Saccharomyces cerevisiae | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results The effect of spontaneous mutations on CUP1 copy number and copper tolerance in Saccharomyces cerevisiae Rohan Sohoni , Gillian G. Schatz , View ORCID Profile Nathaniel P. Sharp doi: https://doi.org/10.1101/2025.11.06.687044 Rohan Sohoni 1 Department of Genetics, University of Wisconsin-Madison , 425-G Henry Mall, Madison, WI, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gillian G. Schatz 1 Department of Genetics, University of Wisconsin-Madison , 425-G Henry Mall, Madison, WI, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nathaniel P. Sharp 1 Department of Genetics, University of Wisconsin-Madison , 425-G Henry Mall, Madison, WI, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nathaniel P. Sharp For correspondence: nathaniel.sharp{at}wisc.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Genomic regions containing tandem duplications may be subject to particularly high rates of copy number mutations due to recombinational repair of DNA damage. Consequently, changes in copy number may be among the most accessible beneficial mutations during evolution in a new environment. In the budding yeast Saccharomyces cerevisiae , the gene CUP1 occurs in multiple tandem copies and encodes a metallothionein protein that is relevant for copper homeostasis. We examined CUP1 copy number in 220 mutation accumulation lines and their ancestors to quantify spontaneous genetic change at this locus. We also measured copper tolerance in the same strains to understand the phenotypic effects of CUP1 copy number change and other mutations. We found that mutations in CUP1 copy number occurred rapidly, with a bias towards the loss of copies. While copper tolerance also declined due to spontaneous mutations, this change was less rapid overall and was only partly driven by CUP1 copy number. Thus, while this locus is highly susceptible to mutation, such mutations may provide an accessible but insufficient evolutionary path towards increased copper resistance. Introduction Different kinds of spontaneous mutations, ranging from single-nucleotide changes to whole-genome duplications, can occur at different rates and vary in their phenotypic impact. Gene duplications likely play an important role in genome evolution, but it is challenging to obtain measures of spontaneous duplication rates that are not influenced by selection [ 1 – 3 ]. There is evidence that tandem duplications are particularly susceptible to copy number mutation due to unequal mitotic recombination and other DNA double-strand break repair pathways [ 4 – 7 ], but the spontaneous rate and direction of such changes has not been well characterized. One way to obtain unbiased estimates of mutation rates is by conducting a mutation accumulation (MA) experiment, where multiple lineages are repeatedly bottlenecked to limit the influence of selection and mutations are identified by genome sequencing [ 8 , 9 ]. In these experiments, copy number changes can be detected bioinformatically, including by examination of relative sequencing coverage at a locus of interest [ 6 , 10 – 15 ]. Mutation accumulation lines also provide opportunities to study whether the genetic changes identified are associated with changes in phenotype. In the budding yeast Saccharomyces cerevisiae , one locus that exhibits natural copy number variation is CUP1 [ 6 , 16 – 18 ]. CUP1 is a small gene encoding a metallothionein protein, which mediates copper ion homeostasis [ 19 ]. The laboratory strain S288c is reported to have 15 tandem copies of this gene, and a sample of natural isolates were found to have 2–18 copies [ 6 ]. The complete absence of CUP1 is not lethal, but strains with one copy or less are described as copper sensitive [ 20 ]. There is evidence that strains with more copies of CUP1 are more copper tolerant and that increased copy number often evolves in high-copper environments [ 6 , 17 , 20 – 23 ]. However, it is unclear how rapidly copy number changes spontaneously, and what the effects of un-selected copy number variation are on copper tolerance. We examined copy number at the CUP1 locus in 220 haploid and diploid lines of S. cerevisiae that each experienced about 1500 generations of MA in standard media [ 24 ], and performed growth inhibition assays to estimate relative copper tolerance in these same lines. Our main aims were to quantify the rate of mutational change in both CUP1 copy number and copper tolerance, as well as the relationship between these traits. We also looked for point mutations within CUP1 and tested whether other mutations known to be present in these strains [ 24 ] were associated with copper tolerance. Materials and methods Yeast strains We conducted our study using the mutation accumulation (MA) lines and corresponding genome sequence data generated from Sharp et al. [ 24 ]. That experiment compared mutation in haploid and diploid versions of the strain SEY6211, where some lines of each ploidy type were genetically modified to delete the gene RDH54 , which is involved in DNA double strand break repair. In our study, we considered possible effects of ploidy and RDH54 status, but our main interest was in the consequences of mutation accumulation. We therefore compared MA lines with their ancestors of the same ploidy and RDH54 status, which remained frozen at –80 C during the MA experiment. CUP1 copy number and point mutations Our estimates of CUP1 copy number are based on Illumina NextSeq data (150-bp paired-end reads), aligned to the reference genome as described in Sharp et al. [ 24 ]. Coverage-based estimates of CUP1 copy number have been found to be strongly correlated with estimates by Southern blotting [ 6 ]. In the reference genome, the CUP1 gene is represented by two copies at positions 212535-212720 and 214533-214718 on chromosome VIII. For each MA and ancestral strain, we used Samtools [ 25 ] to determine the average sequencing coverage at the CUP1 sites, as well as the average coverage on chromosome VIII (using medians produced similar results). We divided CUP1 coverage by chromosome VIII coverage and multiplied by two to obtain an estimate for CUP1 copy number per chromosome VIII. This will reflect the copy number per cell in haploids, and half the copy number per cell in diploids, averaged over homologous chromosomes. In two diploid MA lines, chromosome VIII is known to be present in three copies (trisomy; [ 24 ]), and so we further multiplied our copy number estimates by 1.5 for these two lines when examining the relationship between copy number and copper tolerance. In addition to copy number, mutations within the CUP1 gene could affect copper tolerance, but this region was excluded from a previous analysis of point mutations [ 24 ]. To detect point mutations in CUP1 , we generated pileup files using Samtools [ 25 ] and then applied VarScan [ 26 ], with the minimum variant allele frequency threshold set to zero, allowing all variants to be reported, even those supported by a single read. Copper tolerance We estimated copper tolerance based on growth inhibition on plates, blocking the MA lines by mating type (haploid MATa, haploid MAT α , or diploid) and RDH54 status (wild type, RDH54+ or deleted, rdh54Δ ), with the corresponding ancestral control strains included in each block. For each block, we revived frozen strains in 96 well plates containing 500-750 µL of yeast peptone dextrose (YPD) medium per well, with 48 h of growth at 30 C. We tested copper tolerance on 6 cm diameter plates containing 8 mL of YPD-agar medium by spreading 50-75 µL of yeast culture over each plate using sterile beads. We then placed a sterile filter paper circle (diameter 2.3 cm) in the center of each plate and added 200 µL of copper sulfate pentahydrate in deionized water (312.5 g/L) to the filter circle. For each of the 220 MA lines we obtained three replicate measures of copper tolerance for a total of 657 replicates (growth inhibition zones were unclear on three plates, which were excluded). We also obtained 18 replicate measures of copper tolerance for each of the six types of ancestral control, for a total of 108 replicates. After 24 h of incubation at 30 C, we imaged the plates using a flatbed scanner. We used ImageJ [ 27 ] to determine the area of the zone of yeast growth inhibition around the filter circle on each plate (arbitrary units) and used the reciprocal of this value as an estimate of copper tolerance, i.e., a larger zone of growth inhibition equates to lower tolerance. We analyzed copper tolerance data using linear mixed-effect models fit in R [ 28 ] using packages lme4 [ 29 ] and RLRsim [ 30 ]. Results Our analysis of sequencing coverage in the ancestor strains of the MA experiment revealed an average CUP1 copy number of 10.8 per haploid genome, somewhat less than the estimate of 15 for the reference strain S288c, but within the range observed in natural isolates [ 6 ]. We found no evidence for variation in copy number among the ancestral control samples sequenced (which vary in ploidy and RDH54 status but should otherwise be identical; all F 0.17), and so we treated the mean copy number of those strains as representative of the ancestral condition of all of the MA lines. Mean CUP1 copy number declined significantly during MA going from 10.8 in the ancestor to an average of 8.6 in the MA lines (linear model, effect of MA: t = –3.34, P = 9.81 × 10 −4 ) and ranging from 3.4 to 18.5 ( Fig. 1 ). We found no evidence that the rate of copy number decline differed between groups (model interaction terms: P > 0.66). The rates of change in mean CUP1 copy number per generation (Δ M ) are given in Table 1 . On average, we find a net loss of one CUP1 copy per 709 generations. For individual lines, the fastest observed changes in each direction were one loss per 201 generations and one gain per 194 generations. Since we have only one estimate of CUP1 copy number for each MA line, we cannot formally determine the mutational variance for this trait, but we used the variance among control samples to approximate the error variance. The variance values for each group, following subtraction of the error variance and division by the number of cell divisions (Δ V ), are given in Table 1 . View this table: View inline View popup Download powerpoint Table 1. Trait change per generation of mutation accumulation. Rates of change in mean (Δ M ), variance (Δ V ), and coefficient of variation (CV) per generation for copper tolerance and CUP1 copy number. Download figure Open in new tab Figure 1. Mean CUP1 copy number declines under MA. Each red point represents a CUP1 copy number estimate for an MA line from a given cell type and RDH54 status. Black squares and error bars represent group means and 95% confidence intervals. The mean and 95% confidence interval for the ancestral CUP1 copy number is shown as a horizontal dashed line and band. We found that average copper tolerance declined by about 5% during MA (about 0.003% per generation), with no evidence that this effect was related to cell type or RDH54 status ( Fig. 2 ; linear mixed-effect model, effect of MA: t = –4.04, P = 7.75 × 10 −5 ; interactions with MA: P > 0.42). The rate of decline in copper tolerance per generation of MA (Δ M ) in each group of lines is given in Table 1 . We also tested for genetic variance in copper tolerance among MA lines within each group (mutational variance). We found strong evidence for mutational variance in all groups (all P < 10 −15 except in MAT⌇0 rdh54Δ lines where P = 0.006). Rates of increase in mutational variance per generation of MA (Δ V ) in each group of lines are given in Table 1 . Download figure Open in new tab Figure 2. Mean copper tolerance declines under MA. Each round point represents a copper tolerance estimate for a given MA line or ancestral control replicate. Black squares and error bars represent group means and 95% confidence intervals. Panels depict groups of lines based on cell type and RDH54 status. We examined the relationship between copper tolerance and CUP1 copy number, with tolerance in each MA line standardized by the corresponding ancestral control mean. We found a significant positive correlation between copper tolerance and CUP1 copy number ( Fig. 3A ; r Spearman = 0.21, P = 1.19 × 10 −3 ), but with much variation in copper tolerance remaining unexplained by CUP1 copy number (Pearson r 2 = 2.6%). We also considered whether the rate of copy number change at CUP1 might be related to the rate of copy number change at the highly repetitive rDNA locus, where copy number also declined under MA [ 14 ]. We found a significant positive correlation between CUP1 and rDNA copy number ( Fig. 3B ; r Spearman = 0.15, P = 0.028), suggesting that general mechanisms for copy number change may affect both loci. Decline in rDNA copy number was associated with point mutations in “regulation of cell cycle” genes [ 14 ], but we did not detect such an association for CUP1 copy number ( r Spearman = 0.10, P = 0.15). A previous study of experimental evolution of copper tolerance found no evidence that increased CUP1 copy number had pleiotropic costs for fitness in YPD [ 22 ]; we also found that CUP1 copy number was not significantly correlated with growth rate in YPD (data from [ 24 ]; Fig. 3C ; r Spearman = –0.05, P = 0.44). Growth in YPD was also not significantly correlated with our measures of copper tolerance ( r Spearman = 0.01, P = 0.89). Download figure Open in new tab Figure 3. Associations between CUP1 copy number and other traits. Each red point depicts mean trait values for a given MA line. The blue points and error bars represent the mean and 95% confidence interval for ancestral controls. The Spearman’s rank correlation ( r S ) and P-value ( P ) are shown in each panel. (A) CUP1 copy number was positively associated with copper tolerance. (B) CUP1 copy number was positively associated with rDNA copy number. (C) CUP1 copy number was not significantly associated with growth rate relative to the ancestral control of the same cell type. We did not detect any new point mutations or differences from the reference genome within the CUP1 coding sequence. Given the point mutation rates in these strains [ 24 ], the number of MA generations, the size of CUP1 (185 bp per copy), and assuming 8.6 copies per haploid genome (the post-MA mean), there is a 55% probability that no point mutations would occur in any CUP1 copy during MA. Other genes are known to be upregulated in the presence of high copper, and additional genes have been found to acquire mutations under selection for copper tolerance [ 22 , 31 ]. The MA lines in our study accumulated un-selected mutations, which might affect these previously identified genes by chance. Two MA lines had distinct missense mutations in PCA1 (A789T and A830P), which encodes a copper-binding protein that may be involved in metal ion homeostasis [ 32 ] but was not hit during experimental evolution [ 22 ]. These two strains had significantly below-average copper tolerance compared with the other MA lines ( t = –8.27, P = 0.014), despite not differing from the average in terms of CUP1 copy number ( t = 1.14, P = 0.45). An additional five MA lines had nonsynonymous mutations in other genes implicated in copper tolerance evolution [ 22 ], but these lines did not show significantly reduced tolerance ( t = –1.00, P = 0.36). We also noted that the MA line with the lowest observed copper tolerance ( Fig. 3A ) had a missense mutation in FAB1 (T480I), which encodes a protein involved in vacuolar homeostasis, whose deletion confers metal ion sensitivity [ 33 ]. Increased copy number of chromosome II has also been implicated in copper tolerance, possibly because it carries several relevant genes [ 22 , 34 ]; here, six MA lines had extra copies of that chromosome, and we found suggestive evidence that these strains may have had higher than average copper tolerance (Wilcox test, P = 0.091). Considering aneuploidy more generally (36 of the MA lines are aneuploid for at least one chromosome), we found that chromosome gains were associated with greater copper tolerance ( r Spearman = 0.14, P = 0.033), whereas chromosome losses were not ( r Spearman = –0.01, P = 0.83). The association between tolerance and extra copies of each chromosome is shown in Table 2 . View this table: View inline View popup Download powerpoint Table 2. Relative effects of chromosome gains on mean copper tolerance. Chromosomes where no aneuploidy was observed are omitted. Discussion Although increased CUP1 copy number seems to be common under experimental evolution [ 22 ], we find that there is a mutational bias towards the net loss of copies ( Fig. 1 ). Of the 220 MA lines we examined, only 20 (9.1%) showed CUP1 copy number greater than that of the ancestor, with just 6 lines (2.7%) showing increases of more than 1 copy. Additional copies of CUP1 are likely to be beneficial in the presence of high levels of copper ( Fig 3A ; [ 6 , 20 – 23 ]), and there is no evidence that the presence of additional CUP1 repeats has detrimental pleiotropic consequences for growth rate in the absence of copper ( Fig. 3C ; [ 22 ]). We would therefore expect selection to drive increased copy number in a high-copper environment, but for mutation bias and genetic drift to lead to reduced copy number in a low-copper environment. The net rate of change in CUP1 copy number per generation ( Table 1 ) exceeds the genome-wide average rate of gene duplication or deletion in yeast and other model organisms by three orders of magnitude [ 2 , 35 ]. We are likely underestimating the true rate of mutational change because gains and losses in the same MA lineage will cancel out. In the genetic background we studied, CUP1 is likely to be more susceptible to copy number change than most other genes because it is already present in multiple tandem copies, facilitating unequal crossing over [ 6 ]. In diploids, these events may be more likely to occur between sister chromatids rather than homologous chromosomes [ 36 ]; this is consistent with our observation that the deletion of RDH54 , which is believed to facilitate DNA double-strand break repair between homologs [ 37 ] had no detectable effect on the rate of copy number mutation ( Fig. 1 ). The mutational properties of CUP1 may be similar to those of the highly repetitive rDNA locus, which is present in a tandem array of about 90 copies in the genetic background we studied, and also seems to experience net copy number loss on average, with rarer cases of copy number gain [ 14 ]. Mutational change in rDNA is faster on an absolute basis, but when scaled to the initial copy number, both loci show an average decrease of about 0.01% per generation under mutation accumulation. We also detected a positive correlation across MA lines between CUP1 copy number and rDNA copy number ( Fig. 3B ), suggesting that mutations influencing rDNA copy number maintenance affect other repetitive loci as well. Changes in rDNA were associated with point mutations in “regulation of cell cycle” genes [ 14 ], but we did not detect such an association for CUP1 copy number. In the strains we studied, copper tolerance showed a modest level of mutational variance [ 8 , 38 ]. While CUP1 copy number was a significant predictor of tolerance ( Fig. 3A ), there was plenty of unexplained variation. A trivial reason for this is that measurement error for both copper tolerance and CUP1 copy number will reduce the apparent correlation between these traits (attenuation), but correcting for this bias would have only a small effect on the correlation in this case. Karyotypic changes and mutations at other loci may also have contributed to variation in tolerance (on average, each line had 5.2 non-synonymous mutations). There could also be diminishing returns of additional CUP1 copies if transcripts from high-copy loci interfere with one another [ 39 ]. In natural populations, any initial change in transcript abundance following a gene duplication mutation could be modified by subsequent selection on other loci [ 2 , 12 ]. A previous study found weak evidence that CUP1 expression was related to copy number in experimentally evolved strains [ 22 ]. Our study demonstrates that CUP1 copy number can mutate rapidly, with a bias towards the loss of copies, as expected given its genome architecture. Despite rapid change at CUP1 , the rate of mutational decline in copper tolerance was modest. While changes in CUP1 copy number affected copper tolerance, point mutations in other genes were also associated with reduced tolerance, and copy number increases for several chromosomes were associated with increased tolerance. Increased CUP1 copy number is likely to be an early but insufficient response to selection for copper tolerance. Data availability Raw data and analysis code are available at https://doi.org/10.6084/m9.figshare.30559424.v1 . Funding Research reported in this publication was supported by the University of Wisconsin-Madison Letters and Science Honors Summer Research Apprenticeship program to RS and by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM154954 to NPS. Funder Information Declared National Institute of General Medical Sciences , R35GM154954 References 1. ↵ Ohno S. 1970 Evolution by Gene Duplication . New York, NY : Springer-Verlag . ( doi: 10.1007/978-3-642-86659-3_1) OpenUrl CrossRef 2. ↵ Katju V , Bergthorsson U. 2013 Copy-number changes in evolution: rates, fitness effects and adaptive significance . Front. Genet . 4 , 273 . ( doi: 10.3389/fgene.2013.00273) OpenUrl CrossRef PubMed 3. ↵ Hastings PJ , Lupski JR , Rosenberg SM , Ira G. 2009 Mechanisms of change in gene copy number . Nat. Rev. Genet . 10 , 551 – 564 . ( doi: 10.1038/nrg2593) OpenUrl CrossRef PubMed Web of Science 4. ↵ Anderson RP , Roth JR . 1977 Tandem Genetic Duplications in Phage and Bacteria . Annu. Rev. Microbiol . 31 , 473 – 505 . ( doi: 10.1146/annurev.mi.31.100177.002353) OpenUrl CrossRef PubMed Web of Science 5. Pan D , Zhang L. 2007 Quantifying the major mechanisms of recent gene duplications in the human and mouse genomes: a novel strategy to estimate gene duplication rates . Genome Biol . 8 , R158 . ( doi: 10.1186/gb-2007-8-8-r158) OpenUrl CrossRef PubMed 6. ↵ Zhao Y , Strope PK , Kozmin SG , McCusker JH , Dietrich FS , Kokoska RJ , Petes TD . 2014 Structures of Naturally Evolved CUP1 Tandem Arrays in Yeast Indicate That These Arrays Are Generated by Unequal Nonhomologous Recombination . G3: Genes, Genomes, Genet . 4 , 2259 – 2269 . ( doi: 10.1534/g3.114.012922) OpenUrl CrossRef 7. ↵ Prado F , Cortés-Ledesma F , Huertas P , Aguilera A. 2003 Mitotic recombination in Saccharomyces cerevisiae . Curr. Genet . 42 , 185 – 198 . ( doi: 10.1007/s00294-002-0346-3) OpenUrl CrossRef PubMed Web of Science 8. ↵ Halligan DL , Keightley PD . 2009 Spontaneous Mutation Accumulation Studies in Evolutionary Genetics . Annu Rev Ecol Evol Syst 40 , 151 – 172 . ( doi: 10.1146/annurev.ecolsys.39.110707.173437) OpenUrl CrossRef 9. ↵ Katju V , Bergthorsson U. 2018 Old trade, new tricks: insights into the spontaneous mutation process from the partnering of classical mutation accumulation experiments with high-throughput genomic approaches . Genome Biol Evol , evy252. . ( doi: 10.1093/gbe/evy252) OpenUrl CrossRef 10. ↵ Schrider DR , Houle D , Lynch M , Hahn MW . 2013 Rates and genomic consequences of spontaneous mutational events in Drosophila melanogaster . Genetics 194 , 937 – 54 . ( doi: 10.1534/genetics.113.151670) OpenUrl Abstract / FREE Full Text 11. Keith N et al. 2016 High mutational rates of large-scale duplication and deletion in Daphnia pulex . Genome Res . 26 , 60 – 69 . ( doi: 10.1101/gr.191338.115) OpenUrl Abstract / FREE Full Text 12. ↵ Konrad A , Flibotte S , Taylor J , Waterston RH , Moerman DG , Bergthorsson U , Katju V. 2018 Mutational and transcriptional landscape of spontaneous gene duplications and deletions in Caenorhabditis elegans . Proc National Acad Sci 115 , 201801930 . ( doi: 10.1073/pnas.1801930115) OpenUrl CrossRef 13. Chain FJJ , Flynn JM , Bull JK , Cristescu ME . 2018 Accelerated rates of large-scale mutations in the presence of copper and nickel . Genome Res 29 , 64 – 73 . ( doi: 10.1101/gr.234724.118) OpenUrl CrossRef PubMed 14. ↵ Sharp NP , Smith DR , Driscoll G , Sun K , Vickerman CM , Martin SCT . 2023 Contribution of Spontaneous Mutations to Quantitative and Molecular Variation at the Highly Repetitive rDNA Locus in Yeast . Genome Biol. Evol . 15 , evad179 . ( doi: 10.1093/gbe/evad179) OpenUrl CrossRef PubMed 15. ↵ Gill SE , Chain FJJ . 2023 Very Low Rates of Spontaneous Gene Deletions and Gene Duplications in Dictyostelium discoideum . J. Mol. Evol . 91 , 24 – 32 . ( doi: 10.1007/s00239-022-10081-1) OpenUrl CrossRef PubMed 16. ↵ Loegler V et al. 2025 From genotype to phenotype with 1,086 near telomere-to-telomere yeast genomes . Nature , 1 – 10 . ( doi: 10.1038/s41586-025-09637-0) OpenUrl CrossRef 17. ↵ Warringer J et al. 2011 Trait Variation in Yeast Is Defined by Population History . PLoS Genet . 7 , e1002111 . ( doi: 10.1371/journal.pgen.1002111) OpenUrl CrossRef PubMed 18. ↵ Steenwyk J , Rokas A. 2017 Extensive Copy Number Variation in Fermentation-Related Genes Among Saccharomyces cerevisiae Wine Strains . G3: GenesGenomesGenet . 7 , 1475 – 1485 . ( doi: 10.1534/g3.117.040105) OpenUrl CrossRef 19. ↵ Butt TR , Sternberg EJ , Gorman JA , Clark P , Hamer D , Rosenberg M , Crooke ST . 1984 Copper metallothionein of yeast, structure of the gene, and regulation of expression . Proc. Natl. Acad. Sci . 81 , 3332 – 3336 . ( doi: 10.1073/pnas.81.11.3332) OpenUrl Abstract / FREE Full Text 20. ↵ Fogel S , Welch JW , Cathala G , Karin M. 1983 Gene amplification in yeast: CUP1 copy number regulates copper resistance . Curr. Genet . 7 , 347 – 355 . ( doi: 10.1007/bf00445874) OpenUrl CrossRef PubMed 21. Fogel S , Welch JW . 1982 Tandem gene amplification mediates copper resistance in yeast . Proc. Natl. Acad. Sci . 79 , 5342 – 5346 . ( doi: 10.1073/pnas.79.17.5342) OpenUrl Abstract / FREE Full Text 22. ↵ Gerstein AC , Ono J , Lo DS , Campbell ML , Kuzmin A , Otto SP . 2014 Too Much of a Good Thing: The Unique and Repeated Paths Toward Copper Adaptation . Genetics 199 , 555 – 571 . ( doi: 10.1534/genetics.114.171124) OpenUrl CrossRef PubMed 23. ↵ Adamo GM , Lotti M , Tamás MJ , Brocca S. 2012 Amplification of the CUP1 gene is associated with evolution of copper tolerance in Saccharomyces cerevisiae . Microbiology 158 , 2325 – 2335 . ( doi: 10.1099/mic.0.058024-0) OpenUrl CrossRef PubMed Web of Science 24. ↵ Sharp NP , Sandell L , James CG , Otto SP . 2018 The genome-wide rate and spectrum of spontaneous mutations differ between haploid and diploid yeast . Proc National Acad Sci 115 , 201801040 . ( doi: 10.1073/pnas.1801040115) OpenUrl CrossRef 25. ↵ Li H et al. 2009 The Sequence Alignment/Map format and SAMtools . Bioinformatics 25 , 2078 – 2079 . ( doi: 10.1093/bioinformatics/btp352) OpenUrl CrossRef PubMed Web of Science 26. ↵ Koboldt DC et al. 2012 VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencing . Genome Res 22 , 568 – 576 . ( doi: 10.1101/gr.129684.111) OpenUrl Abstract / FREE Full Text 27. ↵ Schindelin J et al. 2012 Fiji: an open-source platform for biological-image analysis . Nat. Methods 9 , 676 – 682 . ( doi: 10.1038/nmeth.2019) OpenUrl CrossRef PubMed Web of Science 28. ↵ R_Core_Team . 2021 R: A language and environment for statistical computing . R Foundation for Statistical Computing , Vienna, Austria . See https://www.R-project.org/ . 29. ↵ Bates D , Mächler M , Bolker B , Walker S. 2015 Fitting Linear Mixed-Effects Models Using lme4 . J Stat Softw 67 . ( doi: 10.18637/jss.v067.i01) OpenUrl CrossRef 30. ↵ Scheipl F , Greven S , Küchenhoff H. 2008 Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models . Comput. Stat. Data Anal . 52 , 3283 – 3299 . ( doi: 10.1016/j.csda.2007.10.022) OpenUrl CrossRef 31. ↵ Peña MMO , Koch KA , Thiele DJ . 1998 Dynamic Regulation of Copper Uptake and Detoxification Genes in Saccharomyces cerevisiae . Mol. Cell. Biol . 18 , 2514 – 2523 . ( doi: 10.1128/mcb.18.5.2514) OpenUrl Abstract / FREE Full Text 32. ↵ Adle DJ , Sinani D , Kim H , Lee J. 2007 A Cadmium-transporting P1B-type ATPase in Yeast Saccharomyces cerevisiae * . J. Biol. Chem . 282 , 947 – 955 . ( doi: 10.1074/jbc.m609535200) OpenUrl Abstract / FREE Full Text 33. ↵ Bleackley MR , Young BP , Loewen CJR , MacGillivray RTA . 2011 High density array screening to identify the genetic requirements for transition metal tolerance in Saccharomyces cerevisiae . Metallomics 3 , 195 – 205 . ( doi: 10.1039/c0mt00035c) OpenUrl CrossRef PubMed Web of Science 34. ↵ Covo S , Puccia CM , Argueso JL , Gordenin DA , Resnick MA . 2014 The Sister Chromatid Cohesion Pathway Suppresses Multiple Chromosome Gain and Chromosome Amplification . Genetics 196 , 373 – 384 . ( doi: 10.1534/genetics.113.159202) OpenUrl Abstract / FREE Full Text 35. ↵ Lynch M et al. 2008 A genome-wide view of the spectrum of spontaneous mutations in yeast . Proc National Acad Sci 105 , 9272 – 9277 . ( doi: 10.1073/pnas.0803466105) OpenUrl Abstract / FREE Full Text 36. ↵ Song W , Dominska M , Greenwell PW , Petes TD . 2014 Genome-wide high-resolution mapping of chromosome fragile sites in Saccharomyces cerevisiae . Proc. Natl. Acad. Sci . 111 , E2210 – E2218 . ( doi: 10.1073/pnas.1406847111) OpenUrl Abstract / FREE Full Text 37. ↵ Klein HL . 1997 RDH54, a RAD54 homologue in Saccharomyces cerevisiae, is required for mitotic diploid-specific recombination and repair and for meiosis . Genetics 147 , 1533 – 43 . OpenUrl Abstract / FREE Full Text 38. ↵ Houle D. 1998 How should we explain variation in the genetic variance of traits? Genetica 102–103 , 241 . ( doi: 10.1023/a:1017034925212) OpenUrl CrossRef 39. ↵ Cruz C , Houseley J. 2014 Endogenous RNA interference is driven by copy number . eLife 3 , e01581 . ( doi: 10.7554/elife.01581 ) OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted November 07, 2025. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following The effect of spontaneous mutations on CUP1 copy number and copper tolerance in Saccharomyces cerevisiae Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share The effect of spontaneous mutations on CUP1 copy number and copper tolerance in Saccharomyces cerevisiae Rohan Sohoni , Gillian G. Schatz , Nathaniel P. Sharp bioRxiv 2025.11.06.687044; doi: https://doi.org/10.1101/2025.11.06.687044 Share This Article: Copy Citation Tools The effect of spontaneous mutations on CUP1 copy number and copper tolerance in Saccharomyces cerevisiae Rohan Sohoni , Gillian G. Schatz , Nathaniel P. Sharp bioRxiv 2025.11.06.687044; doi: https://doi.org/10.1101/2025.11.06.687044 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Evolutionary Biology Subject Areas All Articles Animal Behavior and Cognition (7636) Biochemistry (17704) Bioengineering (13898) Bioinformatics (41967) Biophysics (21460) Cancer Biology (18599) Cell Biology (25525) Clinical Trials (138) Developmental Biology (13384) Ecology (19909) Epidemiology (2067) Evolutionary Biology (24326) Genetics (15613) Genomics (22512) Immunology (17740) Microbiology (40423) Molecular Biology (17191) Neuroscience (88645) Paleontology (667) Pathology (2835) Pharmacology and Toxicology (4825) Physiology (7646) Plant Biology (15158) Scientific Communication and Education (2046) Synthetic Biology (4302) Systems Biology (9825) Zoology (2271)