Publications by authors named "Aimée M Dudley"

33 Publications

Computational Inference Software for Tetrad Assembly from Randomly Arrayed Yeast Colonies.

G3 (Bethesda) 2019 Jul;9(7):2071-2088

Pacific Northwest Research Institute, Seattle, WA 98122.

We describe an information-theory-based method and associated software for computationally identifying sister spores derived from the same meiotic tetrad. The method exploits specific DNA sequence features of tetrads that result from meiotic centromere and allele segregation patterns. Because the method uses only the genomic sequence, it alleviates the need for tetrad-specific barcodes or other genetic modifications to the strains. Using this method, strains derived from randomly arrayed spores can be efficiently grouped back into tetrads.
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http://dx.doi.org/10.1534/g3.119.400166DOI Listing
July 2019

Exploiting the Autozygome to Support Previously Published Mendelian Gene-Disease Associations: An Update.

Front Genet 2020 31;11:580484. Epub 2020 Dec 31.

Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.

There is a growing interest in standardizing gene-disease associations for the purpose of facilitating the proper classification of variants in the context of Mendelian diseases. One key line of evidence is the independent observation of pathogenic variants in unrelated individuals with similar phenotypes. Here, we expand on our previous effort to exploit the power of autozygosity to produce homozygous pathogenic variants that are otherwise very difficult to encounter in the homozygous state due to their rarity. The identification of such variants in genes with only tentative associations to Mendelian diseases can add to the existing evidence when observed in the context of compatible phenotypes. In this study, we report 20 homozygous variants in 18 genes (, and ) that satisfy the ACMG classification for pathogenic/likely pathogenic if the involved genes had confirmed rather than tentative links to diseases. These variants were selected because they were truncating, founder with compelling segregation or supported by robust functional assays as with the variant that we present its validation using yeast model. Our findings support the previously reported disease associations for these genes and represent a step toward their confirmation.
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http://dx.doi.org/10.3389/fgene.2020.580484DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806527PMC
December 2020

A yeast-based complementation assay elucidates the functional impact of 200 missense variants in human PSAT1.

J Inherit Metab Dis 2020 07 27;43(4):758-769. Epub 2020 Feb 27.

Pacific Northwest Research Institute, Seattle, Washington.

Defects in serine biosynthesis resulting from loss of function mutations in PHGDH, PSAT1, and PSPH cause a set of rare, autosomal recessive diseases known as Neu-Laxova syndrome (NLS) or serine-deficiency disorders. The diseases present with a broad range of phenotypes including lethality, severe neurological manifestations, seizures, and intellectual disability. However, because L-serine supplementation, especially if started prenatally, can ameliorate and in some cases even prevent symptoms, knowledge of pathogenic variants is medically actionable. Here, we describe a functional assay that leverages the evolutionary conservation of an enzyme in the serine biosynthesis pathway, phosphoserine aminotransferase, and the ability of the human protein-coding sequence (PSAT1) to functionally replace its yeast ortholog (SER1). Results from our quantitative, yeast-based assay agree well with clinical annotations and expectations based on the disease literature. Using this assay, we have measured the functional impact of the 199 PSAT1 variants currently listed in ClinVar, gnomAD, and the literature. We anticipate that the assay could be used to comprehensively assess the functional impact of all SNP-accessible amino acid substitution mutations in PSAT1, a resource that could aid variant interpretation and identify potential NLS carriers.
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http://dx.doi.org/10.1002/jimd.12227DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444316PMC
July 2020

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies.

BMC Mol Cell Biol 2019 Dec 19;20(1):59. Epub 2019 Dec 19.

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 2, avenue de l'Université, Esch-sur-Alzette, L-4365, Luxembourg.

Background: Multicellular entities like mammalian tissues or microbial biofilms typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding how this cell-cell and metabolic coupling lead to functionally optimized structures is still limited.

Results: Here, we present a data-driven spatial framework to computationally investigate the development of yeast colonies as such a multicellular structure in dependence on metabolic capacity. For this purpose, we first developed and parameterized a dynamic cell state and growth model for yeast based on on experimental data from homogeneous liquid media conditions. The inferred model is subsequently used in a spatially coarse-grained model for colony development to investigate the effect of metabolic coupling by calibrating spatial parameters from experimental time-course data of colony growth using state-of-the-art statistical techniques for model uncertainty and parameter estimations. The model is finally validated by independent experimental data of an alternative yeast strain with distinct metabolic characteristics and illustrates the impact of metabolic coupling for structure formation.

Conclusions: We introduce a novel model for yeast colony formation, present a statistical methodology for model calibration in a data-driven manner, and demonstrate how the established model can be used to generate predictions across scales by validation against independent measurements of genetically distinct yeast strains.
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http://dx.doi.org/10.1186/s12860-019-0234-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923950PMC
December 2019

Computational Inference Software for Tetrad Assembly from Randomly Arrayed Yeast Colonies.

G3 (Bethesda) 2019 07 9;9(7):2071-2088. Epub 2019 Jul 9.

Pacific Northwest Research Institute, Seattle, WA 98122.

We describe an information-theory-based method and associated software for computationally identifying sister spores derived from the same meiotic tetrad. The method exploits specific DNA sequence features of tetrads that result from meiotic centromere and allele segregation patterns. Because the method uses only the genomic sequence, it alleviates the need for tetrad-specific barcodes or other genetic modifications to the strains. Using this method, strains derived from randomly arrayed spores can be efficiently grouped back into tetrads.
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http://dx.doi.org/10.1534/g3.119.400166DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6643883PMC
July 2019

Selection of Candida albicans trisomy during oropharyngeal infection results in a commensal-like phenotype.

PLoS Genet 2019 05 15;15(5):e1008137. Epub 2019 May 15.

Division of Infectious Diseases, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America.

When the fungus Candida albicans proliferates in the oropharyngeal cavity during experimental oropharyngeal candidiasis (OPC), it undergoes large-scale genome changes at a much higher frequency than when it grows in vitro. Previously, we identified a specific whole chromosome amplification, trisomy of Chr6 (Chr6x3), that was highly overrepresented among strains recovered from the tongues of mice with OPC. To determine the functional significance of this trisomy, we assessed the virulence of two Chr6 trisomic strains and a Chr5 trisomic strain in the mouse model of OPC. We also analyzed the expression of virulence-associated traits in vitro. All three trisomic strains exhibited characteristics of a commensal during OPC in mice. They achieved the same oral fungal burden as the diploid progenitor strain but caused significantly less weight loss and elicited a significantly lower inflammatory host response. In vitro, all three trisomic strains had reduced capacity to adhere to and invade oral epithelial cells and increased susceptibility to neutrophil killing. Whole genome sequencing of pre- and post-infection isolates found that the trisomies were usually maintained. Most post-infection isolates also contained de novo point mutations, but these were not conserved. While in vitro growth assays did not reveal phenotypes specific to de novo point mutations, they did reveal novel phenotypes specific to each lineage. These data reveal that during OPC, clones that are trisomic for Chr5 or Chr6 are selected and they facilitate a commensal-like phenotype.
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http://dx.doi.org/10.1371/journal.pgen.1008137DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538192PMC
May 2019

A polyploid admixed origin of beer yeasts derived from European and Asian wine populations.

PLoS Biol 2019 03 5;17(3):e3000147. Epub 2019 Mar 5.

Pacific Northwest Research Institute, Seattle, Washington, United States of America.

Strains of Saccharomyces cerevisiae used to make beer, bread, and wine are genetically and phenotypically distinct from wild populations associated with trees. The origins of these domesticated populations are not always clear; human-associated migration and admixture with wild populations have had a strong impact on S. cerevisiae population structure. We examined the population genetic history of beer strains and found that ale strains and the S. cerevisiae portion of allotetraploid lager strains were derived from admixture between populations closely related to European grape wine strains and Asian rice wine strains. Similar to both lager and baking strains, ale strains are polyploid, providing them with a passive means of remaining isolated from other populations and providing us with a living relic of their ancestral hybridization. To reconstruct their polyploid origin, we phased the genomes of two ale strains and found ale haplotypes to both be recombinants between European and Asian alleles and to also contain novel alleles derived from extinct or as yet uncharacterized populations. We conclude that modern beer strains are the product of a historical melting pot of fermentation technology.
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http://dx.doi.org/10.1371/journal.pbio.3000147DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6400334PMC
March 2019

Rapid Phenotypic and Genotypic Diversification After Exposure to the Oral Host Niche in .

Genetics 2018 07 3;209(3):725-741. Epub 2018 May 3.

School of Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life Sciences, Tel Aviv University, 69978, Israel.

studies suggest that stress may generate random standing variation and that different cellular and ploidy states may evolve more rapidly under stress. Yet this idea has not been tested with pathogenic fungi growing within their host niche Here, we analyzed the generation of both genotypic and phenotypic diversity during exposure of to the mouse oral cavity. Ploidy, aneuploidy, loss of heterozygosity (LOH), and recombination were determined using flow cytometry and double digest restriction site-associated DNA sequencing. Colony phenotypic changes in size and filamentous growth were evident without selection and were enriched among colonies selected for LOH of the marker. Aneuploidy and LOH occurred on all chromosomes (Chrs), with aneuploidy more frequent for smaller Chrs and whole Chr LOH more frequent for larger Chrs. Large genome shifts in ploidy to haploidy often maintained one or more heterozygous disomic Chrs, consistent with random Chr missegregation events. Most isolates displayed several different types of genomic changes, suggesting that the oral environment rapidly generates diversity In sharp contrast, following propagation, isolates were not enriched for multiple LOH events, except in those that underwent haploidization and/or had high levels of Chr loss. The frequency of events was overall 100 times higher for populations following passage compared with These hyper-diverse isolates likely provide with the ability to adapt rapidly to the diversity of stress environments it encounters inside the host.
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http://dx.doi.org/10.1534/genetics.118.301019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6028260PMC
July 2018

Natural Variation in and Underlie Condition-Specific Growth Defects in .

G3 (Bethesda) 2018 01 4;8(1):239-251. Epub 2018 Jan 4.

Pacific Northwest Research Institute, Seattle, Washington 98122

Despite their ubiquitous use in laboratory strains, naturally occurring loss-of-function mutations in genes encoding core metabolic enzymes are relatively rare in wild isolates of Here, we identify a naturally occurring serine auxotrophy in a sake brewing strain from Japan. Through a cross with a honey wine (white tecc) brewing strain from Ethiopia, we map the minimal medium growth defect to , which encodes 3-phosphoserine aminotransferase and is orthologous to the human disease gene, To investigate the impact of this polymorphism under conditions of abundant external nutrients, we examine growth in rich medium alone or with additional stresses, including the drugs caffeine and rapamycin and relatively high concentrations of copper, salt, and ethanol. Consistent with studies that found widespread effects of different auxotrophies on RNA expression patterns in rich media, we find that the loss-of-function allele dominates the quantitative trait locus (QTL) landscape under many of these conditions, with a notable exacerbation of the effect in the presence of rapamycin and caffeine. We also identify a major-effect QTL associated with growth on salt that maps to the gene encoding the sodium exporter, We demonstrate that the salt phenotype is largely driven by variation in the promoter, which harbors a deletion that removes binding sites for the Mig1 and Nrg1 transcriptional repressors. Thus, our results identify natural variation associated with both coding and regulatory regions of the genome that underlie strong growth phenotypes.
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http://dx.doi.org/10.1534/g3.117.300392DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765352PMC
January 2018

Meeting Report on Experimental Approaches to Evolution and Ecology Using Yeast and Other Model Systems.

G3 (Bethesda) 2017 Aug 16. Epub 2017 Aug 16.

Pacific Northwest Research Institute.

The fourth EMBO-sponsored conference on Experimental Approaches to Evolution and Ecology Using Yeast and Other Model Systems (https://www.embl.de/training/events/2016/EAE16-01/), was held at the EMBL in Heidelberg, Germany, October 19-23, 2016. The conference was organized by Judith Berman (Tel Aviv University), Maitreya Dunham (University of Washington), Jun-Yi Leu (Academia Sinica), and Lars Steinmetz (EMBL Heidelberg and Stanford University). The meeting attracted ~120 researchers from 28 countries and covered a wide range of topics in the fields of genetics, evolutionary biology, and ecology with a unifying focus on yeast as a model system. Attendees enjoyed the Keith Haring inspired yeast florescence microscopy artwork (Figure 1), a unique feature of the meeting since its inception, and the one-minute flash talks that catalyzed discussions at two vibrant poster sessions. The meeting coincided with the 20th anniversary of the publication describing the sequence of the first eukaryotic genome, (Goffeau 1996). Many of the conference talks focused on important questions about what is contained in the genome, how genomes evolve, and the architecture and behavior of communities of phenotypically and genotypically diverse microorganisms. Here, we summarize highlights of the research talks around these themes. Nearly all presentations focused on novel findings, and we refer the reader to relevant manuscripts that have subsequently been published.
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http://dx.doi.org/10.1534/g3.117.300124DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633374PMC
August 2017

Transcriptional Profiling of Biofilm Regulators Identified by an Overexpression Screen in .

G3 (Bethesda) 2017 08 7;7(8):2845-2854. Epub 2017 Aug 7.

Pacific Northwest Research Institute, Seattle, Washington 98122

Biofilm formation by microorganisms is a major cause of recurring infections and removal of biofilms has proven to be extremely difficult given their inherent drug resistance . Understanding the biological processes that underlie biofilm formation is thus extremely important and could lead to the development of more effective drug therapies, resulting in better infection outcomes. Using the yeast as a biofilm model, overexpression screens identified , , , , , and as regulators of biofilm formation. Subsequent RNA-seq analysis of biofilm and nonbiofilm-forming strains revealed that all of the overexpression strains, other than and , were adopting a single differential expression profile, although induced to varying degrees. adopted a separate profile, while the expression profile of reflected the common pattern seen in most of the strains, plus substantial -specific expression changes. We interpret the existence of the common transcriptional pattern seen across multiple, unrelated overexpression strains as reflecting a transcriptional state, that the yeast cell can access through regulatory signaling mechanisms, allowing an adaptive morphological change between biofilm-forming and nonbiofilm states.
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http://dx.doi.org/10.1534/g3.117.042440DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5555487PMC
August 2017

The State of Systems Genetics in 2017.

Cell Syst 2017 01;4(1):7-15

European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany.

Cell Systems invited 16 experts to share their views on the field of systems genetics. In questions repeated in the headings, we asked them to define systems genetics, highlight its relevance to researchers outside the field, discuss what makes a strong systems genetics paper, and paint a picture of where the field is heading in the coming years. Their responses, ordered by the journal but otherwise unedited, make it clear that deciphering genotype to phenotype relationships is a central challenge of systems genetics and will require understanding how networks and higher-order properties of biological systems underlie complex traits. In addition, our experts illuminate the applications and relevance of systems genetics to human disease, the gut microbiome, development of tools that connect the global research community, sustainability, drug discovery, patient-specific disease and network models, and personalized treatments. Finally, a table of suggested reading provides a sample of influential work in the field.
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http://dx.doi.org/10.1016/j.cels.2017.01.005DOI Listing
January 2017

Dissecting Gene Expression Changes Accompanying a Ploidy-Based Phenotypic Switch.

G3 (Bethesda) 2017 01 5;7(1):233-246. Epub 2017 Jan 5.

Pacific Northwest Research Institute, Seattle, Washington 98122

Aneuploidy, a state in which the chromosome number deviates from a multiple of the haploid count, significantly impacts human health. The phenotypic consequences of aneuploidy are believed to arise from gene expression changes associated with the altered copy number of genes on the aneuploid chromosomes. To dissect the mechanisms underlying altered gene expression in aneuploids, we used RNA-seq to measure transcript abundance in colonies of the haploid Saccharomyces cerevisiae strain F45 and two aneuploid derivatives harboring disomies of chromosomes XV and XVI. F45 colonies display complex "fluffy" morphologies, while the disomic colonies are smooth, resembling laboratory strains. Our two disomes displayed similar transcriptional profiles, a phenomenon not driven by their shared smooth colony morphology nor simply by their karyotype. Surprisingly, the environmental stress response (ESR) was induced in F45, relative to the two disomes. We also identified genes whose expression reflected a nonlinear interaction between the copy number of a transcriptional regulatory gene on chromosome XVI, DIG1, and the copy number of other chromosome XVI genes. DIG1 and the remaining chromosome XVI genes also demonstrated distinct contributions to the effect of the chromosome XVI disome on ESR gene expression. Expression changes in aneuploids appear to reflect a mixture of effects shared between different aneuploidies and effects unique to perturbing the copy number of particular chromosomes, including nonlinear copy number interactions between genes. The balance between these two phenomena is likely to be genotype- and environment-specific.
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http://dx.doi.org/10.1534/g3.116.036160DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5217112PMC
January 2017

Independent Origins of Yeast Associated with Coffee and Cacao Fermentation.

Curr Biol 2016 Apr 24;26(7):965-71. Epub 2016 Mar 24.

Pacific Northwest Diabetes Research Institute, Seattle, WA 98122, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA. Electronic address:

Modern transportation networks have facilitated the migration and mingling of previously isolated populations of plants, animals, and insects. Human activities can also influence the global distribution of microorganisms. The best-understood example is yeasts associated with winemaking. Humans began making wine in the Middle East over 9,000 years ago [1, 2]. Selecting favorable fermentation products created specialized strains of Saccharomyces cerevisiae [3, 4] that were transported along with grapevines. Today, S. cerevisiae strains residing in vineyards around the world are genetically similar, and their population structure suggests a common origin that followed the path of human migration [3-7]. Like wine, coffee and cacao depend on microbial fermentation [8, 9] and have been globally dispersed by humans. Theobroma cacao originated in the Amazon and Orinoco basins of Colombia and Venezuela [10], was cultivated in Central America by Mesoamerican peoples, and was introduced to Europeans by Hernán Cortés in 1530 [11]. Coffea, native to Ethiopia, was disseminated by Arab traders throughout the Middle East and North Africa in the 6(th) century and was introduced to European consumers in the 17(th) century [12]. Here, we tested whether the yeasts associated with coffee and cacao are genetically similar, crop-specific populations or genetically diverse, geography-specific populations. Our results uncovered populations that, while defined by niche and geography, also bear signatures of admixture between major populations in events independent of the transport of the plants. Thus, human-associated fermentation and migration may have affected the distribution of yeast involved in the production of coffee and chocolate.
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http://dx.doi.org/10.1016/j.cub.2016.02.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4821677PMC
April 2016

Proteomic Analysis of Dhh1 Complexes Reveals a Role for Hsp40 Chaperone Ydj1 in Yeast P-Body Assembly.

G3 (Bethesda) 2015 Sep 21;5(11):2497-511. Epub 2015 Sep 21.

Molecular and Cellular Biology Program, University of Washington, Seattle, Washington 98195 Pacific Northwest Diabetes Research Institute, Seattle, Washington 98122

P-bodies (PB) are ribonucleoprotein (RNP) complexes that aggregate into cytoplasmic foci when cells are exposed to stress. Although the conserved mRNA decay and translational repression machineries are known components of PB, how and why cells assemble RNP complexes into large foci remain unclear. Using mass spectrometry to analyze proteins immunoisolated with the core PB protein Dhh1, we show that a considerable number of proteins contain low-complexity sequences, similar to proteins highly represented in mammalian RNP granules. We also show that the Hsp40 chaperone Ydj1, which contains an low-complexity domain and controls prion protein aggregation, is required for the formation of Dhh1-GFP foci on glucose depletion. New classes of proteins that reproducibly coenrich with Dhh1-GFP during PB induction include proteins involved in nucleotide or amino acid metabolism, glycolysis, transfer RNA aminoacylation, and protein folding. Many of these proteins have been shown to form foci in response to other stresses. Finally, analysis of RNA associated with Dhh1-GFP shows enrichment of mRNA encoding the PB protein Pat1 and catalytic RNAs along with their associated mitochondrial RNA-binding proteins. Thus, global characterization of PB composition has uncovered proteins important for PB assembly and evidence suggesting an active role for RNA in PB function.
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http://dx.doi.org/10.1534/g3.115.021444DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4632068PMC
September 2015

Aneuploidy: Tolerating Tolerance.

Curr Biol 2015 Aug;25(17):R771-3

Pacific Northwest Diabetes Research Institute, Seattle, WA 98122, USA. Electronic address:

Individuals, and cells, vary in their ability to tolerate aneuploidy, an unbalanced chromosome complement. Tolerance mechanisms can be karyotype-specific or general. General tolerance mechanisms may allow cells to benefit from the phenotypic plasticity conferred by access to multiple aneuploid states.
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http://dx.doi.org/10.1016/j.cub.2015.06.056DOI Listing
August 2015

Allelic variation, aneuploidy, and nongenetic mechanisms suppress a monogenic trait in yeast.

Genetics 2015 Jan 13;199(1):247-62. Epub 2014 Nov 13.

Pacific Northwest Diabetes Research Institute, Seattle, Washington 98122

Clinically relevant features of monogenic diseases, including severity of symptoms and age of onset, can vary widely in response to environmental differences as well as to the presence of genetic modifiers affecting the trait's penetrance and expressivity. While a better understanding of modifier loci could lead to treatments for Mendelian diseases, the rarity of individuals harboring both a disease-causing allele and a modifying genotype hinders their study in human populations. We examined the genetic architecture of monogenic trait modifiers using a well-characterized yeast model of the human Mendelian disease classic galactosemia. Yeast strains with loss-of-function mutations in the yeast ortholog (GAL7) of the human disease gene (GALT) fail to grow in the presence of even small amounts of galactose due to accumulation of the same toxic intermediates that poison human cells. To isolate and individually genotype large numbers of the very rare (∼0.1%) galactose-tolerant recombinant progeny from a cross between two gal7Δ parents, we developed a new method, called "FACS-QTL." FACS-QTL improves upon the currently used approaches of bulk segregant analysis and extreme QTL mapping by requiring less genome engineering and strain manipulation as well as maintaining individual genotype information. Our results identified multiple distinct solutions by which the monogenic trait could be suppressed, including genetic and nongenetic mechanisms as well as frequent aneuploidy. Taken together, our results imply that the modifiers of monogenic traits are likely to be genetically complex and heterogeneous.
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http://dx.doi.org/10.1534/genetics.114.170563DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4286688PMC
January 2015

Unidirectional P-body transport during the yeast cell cycle.

PLoS One 2014 11;9(6):e99428. Epub 2014 Jun 11.

Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, United States of America; Pacific Northwest Diabetes Research Institute, Seattle, Washington, United States of America.

P-bodies belong to a large family of RNA granules that are associated with post-transcriptional gene regulation, conserved from yeast to mammals, and influence biological processes ranging from germ cell development to neuronal plasticity. RNA granules can also transport RNAs to specific locations. Germ granules transport maternal RNAs to the embryo, and neuronal granules transport RNAs long distances to the synaptic dendrites. Here we combine microfluidic-based fluorescent microscopy of single cells and automated image analysis to follow p-body dynamics during cell division in yeast. Our results demonstrate that these highly dynamic granules undergo a unidirectional transport from the mother to the daughter cell during mitosis as well as a constrained "hovering" near the bud site half an hour before the bud is observable. Both behaviors are dependent on the Myo4p/She2p RNA transport machinery. Furthermore, single cell analysis of cell size suggests that PBs play an important role in daughter cell growth under nutrient limiting conditions.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0099428PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053424PMC
February 2015

BEST: barcode enabled sequencing of tetrads.

J Vis Exp 2014 May 1(87). Epub 2014 May 1.

Pacific Northwest Diabetes Research Institute;

Tetrad analysis is a valuable tool for yeast genetics, but the laborious manual nature of the process has hindered its application on large scales. Barcode Enabled Sequencing of Tetrads (BEST)1 replaces the manual processes of isolating, disrupting and spacing tetrads. BEST isolates tetrads by virtue of a sporulation-specific GFP fusion protein that permits fluorescence-activated cell sorting of tetrads directly onto agar plates, where the ascus is enzymatically digested and the spores are disrupted and randomly arrayed by glass bead plating. The haploid colonies are then assigned sister spore relationships, i.e. information about which spores originated from the same tetrad, using molecular barcodes read during genotyping. By removing the bottleneck of manual dissection, hundreds or even thousands of tetrads can be isolated in minutes. Here we present a detailed description of the experimental procedures required to perform BEST in the yeast Saccharomyces cerevisiae, starting with a heterozygous diploid strain through the isolation of colonies derived from the haploid meiotic progeny.
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http://dx.doi.org/10.3791/51401DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4172027PMC
May 2014

Identification and characterization of a drug-sensitive strain enables puromycin-based translational assays in Saccharomyces cerevisiae.

Yeast 2014 May 19;31(5):167-78. Epub 2014 Mar 19.

Institute for Systems Biology, Seattle, WA, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA.

Puromycin is an aminonucleoside antibiotic with structural similarity to aminoacyl tRNA. This structure allows the drug to bind the ribosomal A site and incorporate into nascent polypeptides, causing chain termination, ribosomal subunit dissociation and widespread translational arrest at high concentrations. In contrast, at sufficiently low concentrations, puromycin incorporates primarily at the C-terminus of proteins. While a number of techniques utilize puromycin incorporation as a tool for probing translational activity in vivo, these methods cannot be applied in yeasts that are insensitive to puromycin. Here, we describe a mutant strain of the yeast Saccharomyces cerevisiae that is sensitive to puromycin and characterize the cellular response to the drug. Puromycin inhibits the growth of yeast cells mutant for erg6∆, pdr1∆ and pdr3∆ (EPP) on both solid and liquid media. Puromycin also induces the aggregation of the cytoplasmic processing body component Edc3 in the mutant strain. We establish that puromycin is rapidly incorporated into yeast proteins and test the effects of puromycin on translation in vivo. This study establishes the EPP strain as a valuable tool for implementing puromycin-based assays in yeast, which will enable new avenues of inquiry into protein production and maturation.
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http://dx.doi.org/10.1002/yea.3007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4013229PMC
May 2014

Quantitative analysis of colony morphology in yeast.

Biotechniques 2014 Jan;56(1):18-27

Pacific Northwest Diabetes Research Institute, Seattle, WA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA.

Microorganisms often form multicellular structures such as biofilms and structured colonies that can influence the organism's virulence, drug resistance, and adherence to medical devices. Phenotypic classification of these structures has traditionally relied on qualitative scoring systems that limit detailed phenotypic comparisons between strains. Automated imaging and quantitative analysis have the potential to improve the speed and accuracy of experiments designed to study the genetic and molecular networks underlying different morphological traits. For this reason, we have developed a platform that uses automated image analysis and pattern recognition to quantify phenotypic signatures of yeast colonies. Our strategy enables quantitative analysis of individual colonies, measured at a single time point or over a series of time-lapse images, as well as the classification of distinct colony shapes based on image-derived features. Phenotypic changes in colony morphology can be expressed as changes in feature space trajectories over time, thereby enabling the visualization and quantitative analysis of morphological development. To facilitate data exploration, results are plotted dynamically through an interactive Yeast Image Analysis web application (YIMAA; http://yimaa.cs.tut.fi) that integrates the raw and processed images across all time points, allowing exploration of the image-based features and principal components associated with morphological development.
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http://dx.doi.org/10.2144/000114123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3996921PMC
January 2014

POMO--Plotting Omics analysis results for Multiple Organisms.

BMC Genomics 2013 Dec 24;14:918. Epub 2013 Dec 24.

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg, Luxembourg.

Background: Systems biology experiments studying different topics and organisms produce thousands of data values across different types of genomic data. Further, data mining analyses are yielding ranked and heterogeneous results and association networks distributed over the entire genome. The visualization of these results is often difficult and standalone web tools allowing for custom inputs and dynamic filtering are limited.

Results: We have developed POMO (http://pomo.cs.tut.fi), an interactive web-based application to visually explore omics data analysis results and associations in circular, network and grid views. The circular graph represents the chromosome lengths as perimeter segments, as a reference outer ring, such as cytoband for human. The inner arcs between nodes represent the uploaded network. Further, multiple annotation rings, for example depiction of gene copy number changes, can be uploaded as text files and represented as bar, histogram or heatmap rings. POMO has built-in references for human, mouse, nematode, fly, yeast, zebrafish, rice, tomato, Arabidopsis, and Escherichia coli. In addition, POMO provides custom options that allow integrated plotting of unsupported strains or closely related species associations, such as human and mouse orthologs or two yeast wild types, studied together within a single analysis. The web application also supports interactive label and weight filtering. Every iterative filtered result in POMO can be exported as image file and text file for sharing or direct future input.

Conclusions: The POMO web application is a unique tool for omics data analysis, which can be used to visualize and filter the genome-wide networks in the context of chromosomal locations as well as multiple network layouts. With the several illustration and filtering options the tool supports the analysis and visualization of any heterogeneous omics data analysis association results for many organisms. POMO is freely available and does not require any installation or registration.
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http://dx.doi.org/10.1186/1471-2164-14-918DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3880012PMC
December 2013

Genomic sequence diversity and population structure of Saccharomyces cerevisiae assessed by RAD-seq.

G3 (Bethesda) 2013 Dec 9;3(12):2163-71. Epub 2013 Dec 9.

Institute for Systems Biology, Seattle, Washington 98109.

The budding yeast Saccharomyces cerevisiae is important for human food production and as a model organism for biological research. The genetic diversity contained in the global population of yeast strains represents a valuable resource for a number of fields, including genetics, bioengineering, and studies of evolution and population structure. Here, we apply a multiplexed, reduced genome sequencing strategy (restriction site-associated sequencing or RAD-seq) to genotype a large collection of S. cerevisiae strains isolated from a wide range of geographical locations and environmental niches. The method permits the sequencing of the same 1% of all genomes, producing a multiple sequence alignment of 116,880 bases across 262 strains. We find diversity among these strains is principally organized by geography, with European, North American, Asian, and African/S. E. Asian populations defining the major axes of genetic variation. At a finer scale, small groups of strains from cacao, olives, and sake are defined by unique variants not present in other strains. One population, containing strains from a variety of fermentations, exhibits high levels of heterozygosity and a mixture of alleles from European and Asian populations, indicating an admixed origin for this group. We propose a model of geographic differentiation followed by human-associated admixture, primarily between European and Asian populations and more recently between European and North American populations. The large collection of genotyped yeast strains characterized here will provide a useful resource for the broad community of yeast researchers.
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http://dx.doi.org/10.1534/g3.113.007492DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852379PMC
December 2013

Aneuploidy underlies a multicellular phenotypic switch.

Proc Natl Acad Sci U S A 2013 Jul 28;110(30):12367-72. Epub 2013 Jun 28.

Institute for Systems Biology, Seattle, WA 98109, USA.

Although microorganisms are traditionally used to investigate unicellular processes, the yeast Saccharomyces cerevisiae has the ability to form colonies with highly complex, multicellular structures. Colonies with the "fluffy" morphology have properties reminiscent of bacterial biofilms and are easily distinguished from the "smooth" colonies typically formed by laboratory strains. We have identified strains that are able to reversibly toggle between the fluffy and smooth colony-forming states. Using a combination of flow cytometry and high-throughput restriction-site associated DNA tag sequencing, we show that this switch is correlated with a change in chromosomal copy number. Furthermore, the gain of a single chromosome is sufficient to switch a strain from the fluffy to the smooth state, and its subsequent loss to revert the strain back to the fluffy state. Because copy number imbalance of six of the 16 S. cerevisiae chromosomes and even a single gene can modulate the switch, our results support the hypothesis that the state switch is produced by dosage-sensitive genes, rather than a general response to altered DNA content. These findings add a complex, multicellular phenotype to the list of molecular and cellular traits known to be altered by aneuploidy and suggest that chromosome missegregation can provide a quick, heritable, and reversible mechanism by which organisms can toggle between phenotypes.
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http://dx.doi.org/10.1073/pnas.1301047110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3725063PMC
July 2013

High-throughput tetrad analysis.

Nat Methods 2013 Jul 12;10(7):671-5. Epub 2013 May 12.

Institute for Systems Biology, Seattle, Washington, USA.

Tetrad analysis has been a gold-standard genetic technique for several decades. Unfortunately, the need to manually isolate, disrupt and space tetrads has relegated its application to small-scale studies and limited its integration with high-throughput DNA sequencing technologies. We have developed a rapid, high-throughput method, called barcode-enabled sequencing of tetrads (BEST), that uses (i) a meiosis-specific GFP fusion protein to isolate tetrads by FACS and (ii) molecular barcodes that are read during genotyping to identify spores derived from the same tetrad. Maintaining tetrad information allows accurate inference of missing genetic markers and full genotypes of missing (and presumably nonviable) individuals. An individual researcher was able to isolate over 3,000 yeast tetrads in 3 h, an output equivalent to that of almost 1 month of manual dissection. BEST is transferable to other microorganisms for which meiotic mapping is significantly more laborious.
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http://dx.doi.org/10.1038/nmeth.2479DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3696418PMC
July 2013

Genetics. Systems genetics.

Science 2011 Feb;331(6020):1015-6

Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA.

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http://dx.doi.org/10.1126/science.1203869DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4042627PMC
February 2011

Surface plasmon resonance biosensor for rapid label-free detection of microribonucleic acid at subfemtomole level.

Anal Chem 2010 Dec 19;82(24):10110-5. Epub 2010 Nov 19.

Institute of Photonics and Electronics, Academy of Sciences of the Czech Republic, Chaberská 57, 18251 Prague, Czech Republic.

Microribonucleic acids (miRNAs) have been linked with various regulatory functions and disorders, such as cancers and heart diseases. They, therefore, present an important target for detection technologies for future medical diagnostics. We report here a novel method for rapid and sensitive miRNA detection and quantitation using surface plasmon resonance (SPR) sensor technology and a DNA*RNA antibody-based assay. The approach takes advantage of a novel high-performance portable SPR sensor instrument for spectroscopy of surface plasmons based on a special diffraction grating called a surface plasmon coupler and disperser (SPRCD). The surface of the grating is functionalized with thiolated DNA oligonucleotides which specifically capture miRNA from a liquid sample without amplification. Subsequently, an antibody that recognizes DNA*RNA hybrids is introduced to bind to the DNA*RNA complex and enhance sensor response to the captured miRNA. This approach allows detection of miRNA in less than 30 min at concentrations down to 2 pM with an absolute amount at high attomoles. The methodology is evaluated for analysis of miRNA from mouse liver tissues and is found to yield results which agree well with those provided by the quantitative polymerase chain reaction (qPCR).
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http://dx.doi.org/10.1021/ac102131sDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3021551PMC
December 2010

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images.

BMC Bioinformatics 2010 May 13;11:248. Epub 2010 May 13.

Department of Signal Processing, Tampere University of Technology, Tampere, 33101, Finland.

Background: Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed.

Results: To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies.

Conclusions: These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.
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http://dx.doi.org/10.1186/1471-2105-11-248DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098061PMC
May 2010

Learning a prior on regulatory potential from eQTL data.

PLoS Genet 2009 Jan 30;5(1):e1000358. Epub 2009 Jan 30.

Computer Science Department, Stanford University, Stanford, California, United States of America.

Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of "regulatory features"-including the function of the gene and the conservation, type, and position of genetic polymorphisms-that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3-a sequence-specific RNA binding protein-and P-bodies-cytoplasmic structures that regulate translation and RNA stability-as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway.
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http://dx.doi.org/10.1371/journal.pgen.1000358DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2627940PMC
January 2009

Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions.

Genome Biol 2008 22;9(9):R140. Epub 2008 Sep 22.

Bioinformatics graduate Program, Boston University, Boston, MA 02215, USA.

Background: Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only begun to be explored.

Results: In this study, we measured growth phenotypes of 465 Saccharomyces cerevisiae gene deletion mutants under 16 metabolically relevant conditions and integrated them with the corresponding flux balance model predictions. We first used discordance between experimental results and model predictions to guide a stage of experimental refinement, which resulted in a significant improvement in the quality of the experimental data. Next, we used discordance still present in the refined experimental data to assess the reliability of yeast metabolism models under different conditions. In addition to estimating predictive capacity based on growth phenotypes, we sought to explain these discordances by examining predicted flux distributions visualized through a new, freely available platform. This analysis led to insight into the glycerol utilization pathway and the potential effects of metabolic shortcuts on model results. Finally, we used model predictions and experimental data to discriminate between alternative raffinose catabolism routes.

Conclusions: Our study demonstrates how a new level of integration between high throughput measurements and flux balance model predictions can improve understanding of both experimental and computational results. The added value of a joint analysis is a more reliable platform for specific testing of biological hypotheses, such as the catabolic routes of different carbon sources.
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http://dx.doi.org/10.1186/gb-2008-9-9-r140DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2592718PMC
January 2009