Domains of the SFL1 protein of yeasts are homologous to Myc oncoproteins or yeast heat-shock transcription factor

Fujita, Atsushi; Kikuchi, Yo; Kuhara, Satoru; Misumi, Yoshio; Matsumoto, Seiji; Kobayashi, Harumi

doi:10.1016/0378-1119(89)90424-1

Cited by 66 publications

(22 citation statements)

References 34 publications

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“…Indeed, we detected two QTL (Figure S4), each of which contains a gene known to modify flocculation: the FLO1 allele (Hodgson et al 1985) from the S96 background (disrupted in SK1 according to our sequencing data) and the SFL1 allele (Fujita et al 1989) from the SK1 background (which harbors a premature stop codon at amino acid 477 in SK1). For SFL1 , the calculated maximum LOD score in the QTL was within the gene and even close to its premature (likely causative) stop codon in SK1.…”

Section: Resultsmentioning

confidence: 94%

An Evaluation of High-Throughput Approaches to QTL Mapping in Saccharomyces cerevisiae

et al. 2014

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Dissecting the molecular basis of quantitative traits is a significant challenge and is essential for understanding complex diseases. Even in model organisms, precisely determining causative genes and their interactions has remained elusive, due in part to difficulty in narrowing intervals to single genes and in detecting epistasis or linked quantitative trait loci. These difficulties are exacerbated by limitations in experimental design, such as low numbers of analyzed individuals or of polymorphisms between parental genomes. We address these challenges by applying three independent high-throughput approaches for QTL mapping to map the genetic variants underlying 11 phenotypes in two genetically distant Saccharomyces cerevisiae strains, namely (1) individual analysis of >700 meiotic segregants, (2) bulk segregant analysis, and (3) reciprocal hemizygosity scanning, a new genome-wide method that we developed. We reveal differences in the performance of each approach and, by combining them, identify eight polymorphic genes that affect eight different phenotypes: colony shape, flocculation, growth on two nonfermentable carbon sources, and resistance to two drugs, salt, and high temperature. Our results demonstrate the power of individual segregant analysis to dissect QTL and address the underestimated contribution of interactions between variants. We also reveal confounding factors like mutations and aneuploidy in pooled approaches, providing valuable lessons for future designs of complex trait mapping studies.

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Section: Resultsmentioning

confidence: 94%

An Evaluation of High-Throughput Approaches to QTL Mapping in Saccharomyces cerevisiae

et al. 2014

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“…4D). This premature stop codon truncates SFL1 prior to the sequence encoding a domain (AA 571–658) that is strongly similar to a conserved region in Myc oncoproteins [48]. Previous studies have identified hyperactive filamentation in a mutant of the CEN.PK 113-7D background upon introduction of a premature translational stop at SFL1 codon 320 (Q320-stop) [51].…”

Section: Resultsmentioning

confidence: 99%

“…SFL1 encodes a transcriptional repressor of pseudohyphal growth that functions by binding to the FLO11 promoter, thereby blocking transcriptional activation [24], [25], [48]–[51]. Consistent with its function in repressing FLO gene expression, deletion of SFL1 results in exaggerated invasive growth [28], [32], [48]. Interestingly, the SK1 strain contains an allelic variant of SFL1 with respect to S288C-derived strains, resulting in the conversion of codon 477 (CAA encoding glutamine) to a TAA stop codon (Fig.…”

Section: Resultsmentioning

confidence: 99%

Pooled Segregant Sequencing Reveals Genetic Determinants of Yeast Pseudohyphal Growth

et al. 2014

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The pseudohyphal growth response is a dramatic morphological transition and presumed foraging mechanism wherein yeast cells form invasive and surface-spread multicellular filaments. Pseudohyphal growth has been studied extensively as a model of conserved signaling pathways controlling stress responses, cell morphogenesis, and fungal virulence in pathogenic fungi. The genetic contribution to pseudohyphal growth is extensive, with at least 500 genes required for filamentation; as such, pseudohyphal growth is a complex trait, and linkage analysis is a classical means to dissect the genetic basis of a complex phenotype. Here, we implemented linkage analysis by crossing each of two filamentous strains of Saccharomyces cerevisiae (Σ1278b and SK1) with an S288C-derived non-filamentous strain. We then assayed meiotic progeny for filamentation and mapped allelic linkage in pooled segregants by whole-genome sequencing. This analysis identified linkage in a cohort of genes, including the negative regulator SFL1, which we find contains a premature stop codon in the invasive SK1 background. The S288C allele of the polarity gene PEA2, encoding Leu409 rather than Met, is linked with non-invasion. In Σ1278b, the pea2-M409L mutation results in decreased invasive filamentation and elongation, diminished activity of a Kss1p MAPK pathway reporter, decreased unipolar budding, and diminished binding of the polarisome protein Spa2p. Variation between SK1 and S288C in the mitochondrial inner membrane protein Mdm32p at residues 182 and 262 impacts invasive growth and mitochondrial network structure. Collectively, this work identifies new determinants of pseudohyphal growth, while highlighting the coevolution of protein complexes and organelle structures within a given genome in specifying complex phenotypes.

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“…INO1 memory requires a cis -acting Memory Recruitment Sequence (MRS) in the promoter, to which Sfl1 binds specifically during memory (D'Urso et al 2016). Sfl1 has a Heat Shock Factor-like DNA binding domain but has been characterized as a transcriptional repressor (Fujita et al 1989; Robertson and Fink 1998; Song and Carlson 1998). Loss of Sfl1 disrupts all aspect of INO1 memory.…”

Section: Molecular Mechanisms Of Epigenetic Transcriptional Memorymentioning

confidence: 99%

Epigenetic transcriptional memory

2016

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Organisms alter gene expression to adapt to changes in environmental conditions such as temperature, nutrients, inflammatory signals and stress (Gialitakis et al. 2010; Conrath 2011; Avramova 2015; Solé et al. 2015; Ho and Gasch 2015; Bevington et al. 2016; Hilker et al. 2016). In some cases, organisms can “remember” a previous environmental condition and adapt to that condition more rapidly in the future (Gems and Partridge 2008). Epigenetic transcriptional memory in response to a previous stimulus can produce heritable changes in the response of an organism to the same stimulus, quantitatively or qualitatively altering changes in gene expression (Brickner et al. 2007; Light et al. 2010; Light et al. 2013; D'Urso and Brickner 2014; Avramova 2015; D'Urso et al. 2016). The role of chromatin changes in controlling binding of poised RNAPII during memory are conserved from yeast to humans. Here we discuss epigenetic transcriptional memory in different systems and our current understanding of its molecular basis. Our recent work with a well-characterized model for transcriptional memory demonstrated that memory is initiated by binding of a transcription factor, leading to essential changes in chromatin structure and allowing binding of a poised form of RNA polymerase II, promoting the rate of future re-activation (D'Urso et al. 2016).

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Domains of the SFL1 protein of yeasts are homologous to Myc oncoproteins or yeast heat-shock transcription factor

Cited by 66 publications

References 34 publications

An Evaluation of High-Throughput Approaches to QTL Mapping in Saccharomyces cerevisiae

An Evaluation of High-Throughput Approaches to QTL Mapping in Saccharomyces cerevisiae

Pooled Segregant Sequencing Reveals Genetic Determinants of Yeast Pseudohyphal Growth

Epigenetic transcriptional memory

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