Application of SNPs for assessing biodiversity and phylogeny among yeast strains

Quantitative traits are conditioned by several genetic determinants. Since such genes influence many important complex traits in various organisms, the identification of quantitative trait loci (QTLs) is of major interest, but still encounters serious difficulties. We detected four linked genes within one QTL, which participate in controlling sporulation efficiency in Saccharomyces cerevisiae. Following the identification of single nucleotide polymorphisms by comparing the sequences of 145 genes between the parental strains SK1 and S288c, we analyzed the segregating progeny of the cross between them. Through reciprocal hemizygosity analysis, four genes, RAS2, PMS1, SWS2, and FKH2, located in a region of 60 kilobases on Chromosome 14, were found to be associated with sporulation efficiency. Three of the four “high” sporulation alleles are derived from the “low” sporulating strain. Two of these sporulation-related genes were verified through allele replacements. For RAS2, the causative variation was suggested to be a single nucleotide difference in the upstream region of the gene. This quantitative trait nucleotide accounts for sporulation variability among a set of ten closely related winery yeast strains. Our results provide a detailed view of genetic complexity in one “QTL region” that controls a quantitative trait and reports a single nucleotide polymorphism-trait association in wild strains. Moreover, these findings have implications on QTL identification in higher eukaryotes.

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“…In a previous study [26], we compared various S. cerevisiae strains, including ten strains from a winery in California [27].…”

Section: Resultsmentioning

confidence: 99%

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

et al. 2006

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“…Other sources of heterogeneity include the long evolutionary history potentially accompanied with inconsistent substitution rates of different gene sets that could be associated with unique ecological shifts such as association with hosts (Kurtzman and Robnett, 2003;Scannell et al, 2011). The emergence and maintenance of haploid lineages via what appears to be long-term asexual reproduction in some Candida species is associated with shifting rates of evolution (Ben-Ari et al, 2005;Webster and Hurst, 2012), contributing additional complexity to the solution of the yeast phylogeny. Results of signal and noise analysis on the five assayed markers under alternative models disclosed some issues behind the unresolved phylogeny of the haploid Candida clade and pointed out an efficient approach toward future phylogenetic experimental design on this group of fungi.…”

Section: Discussionmentioning

confidence: 99%

The impact of incorporating molecular evolutionary model into predictions of phylogenetic signal and noise

Wang

López-Giráldez

et al. 2014

Front. Ecol. Evol.

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Phylogenetic inference can be improved by the development and use of better models for inference given the data available, or by gathering more appropriate data given the potential inferences to be made. Numerous studies have demonstrated the crucial importance of selecting a best-fit model to conducting accurate phylogenetic inference given a data set, explicitly revealing how model choice affects the results of phylogenetic inferences. However, the importance of specifying a correct model of evolution for predictions of the best data to be gathered has never been examined. Here, we extend analyses of phylogenetic signal and noise that predict the potential to resolve nodes in a phylogeny to incorporate all time-reversible Markov models of nucleotide substitution. Extending previous results on the canonical four-taxon tree, our theory yields an analytical method that uses estimates of the rates of evolution and the model of molecular evolution to predict the distribution of signal, noise, and polytomy. We applied our methods to a study of 29 taxa of the yeast genus Candida and allied members to predict the power of five markers, COX2, ACT1, RPB1, RPB2, and D1/D2 LSU, to resolve a poorly supported backbone node corresponding to a clade of haploid Candida species, as well as 19 other nodes that are reasonably short and at least moderately deep in the consensus tree. The use of simple, unrealistic models that did not take into account transition/transversion rate differences led to some discrepancies in predictions, but overall our results demonstrate that predictions of signal and noise in phylogenetics are fairly robust to model specification.

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“…Although with this method, unique SNPs will not be identified, the most polymorphic SNPs should be disclosed. This approach, especially if performed on a large scale and based on several thousand SNPs, can avoid the bias caused by other approaches to SNP determination (Ben-Ari et al 2005).…”

Section: Snps Identification Strategymentioning

confidence: 99%

Development of a large set of SNP markers for assessing phylogenetic relationships between the olive cultivars composing the Israeli olive germplasm collection

et al. 2015

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The olive (Olea europaea L.) was domesticated in the Mediterranean area over 6000 years ago and is currently one of the area's most important oleaginous crops. Due to its economic, cultural and ecological importance, breeding programs aimed at obtaining new olive cultivars have been developed in most olive-producing countries. An efficient breeding program requires a large and genetically variable germplasm collection. In this study, we used nextgeneration sequencing technology for the identification of 145,974 single nucleotide polymorphism (SNPs) loci. A subset of 138 SNPs was then used to analyze the genetic relationships between 119 cultivars making up most of the Israeli germplasm collection. The various cultivars did not cluster according to their geographic origin but rather showed a high correlation with their function (oil, table or dual purpose). Comparison of genetic diversity between 15 cultivars using SSRs and SNPs revealed that for the purposes of analyzing genetic variation between olive cultivars, the SSR marker seems more suitable. However, based on the analysis of several trees of the same cultivar sampled from different nurseries, the SNP marker proved to be a more reliable criterion for cultivar identification. This study presents the most comprehensive SNP analysis of olive phylogeny to date. Based on the rapid development of SNP genotyping methods over the last few years, we believe that in the near future, we will be able to genotype many sample genomes using the appropriate SNPs at a reasonably low cost. Therefore, we can expect that in the future, SNPs will definitely be the marker of choice for biodiversity analysis as well as for gene cloning and QTL identification in olives.

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Application of SNPs for assessing biodiversity and phylogeny among yeast strains

Cited by 29 publications

References 29 publications

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

The impact of incorporating molecular evolutionary model into predictions of phylogenetic signal and noise

Development of a large set of SNP markers for assessing phylogenetic relationships between the olive cultivars composing the Israeli olive germplasm collection

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