TheHittingerLab

TheHittingerLab

The Hittinger Lab

The Hittinger Lab Lightening Journal Club is designed to help us review and share a bundle of journals all at once on a quarterly or half-year basis. Each person has 2-3 journals they are responsible for, and we do a round-robin style description with questions and discussions.

Friday, April 8, 2016 - participants are listed alphabeticallly and the articles they brought to the discussion as they provided them.

Christina

  1. Evolution of moth sex pheromone composition by a single amino acid substitution in a fatty acid desaturate Aleš Bucek et al. (2015) PNAS http://www.ncbi.nlm.nih.gov/pubmed/?term=26417103
  2. Interallelic interaction and gene regulation in budding yeast http://www.ncbi.nlm.nih.gov/pubmed/?term=27044105
  3. Social wasps are a Saccharomyces mating nest http://www.ncbi.nlm.nih.gov/pubmed/?term=26787874
  4. Chromosome position determines the success of double-strand break repair http://www.ncbi.nlm.nih.gov/pubmed/?term=26715752
  5. Systematic analysis of asymmetric partitioning of yeast proteome between mother and daughter cells reveals “aging factors” and mechanism of lifespan asymmetry http://www.ncbi.nlm.nih.gov/pubmed/?term=26351681

Dana

  1. Responses of Saccharomyces cerevisiae strains from different origins to elevated iron concentrations Martinez-Garay et al. (2016), Applied and Environmental Microbiology
  2. Competition-mediated feedbacks in experimental multispecies epizootics Dallas et al. (2016), Ecology
  3. The relative importance of trait vs. genetic differentiation for the outcome of interactions among plan genotypes Abbott and Stachowicz (2016), Ecology
  4. Transcriptome analysis of the painted lady butterfly, Vanessa cardui during wing color pattern development Connahs et al. (2016), BMC Genomics
  5. Does biodiversity protect humans against infectious disease? – Levi et al. (2016), Ecology

Drew - not present, but participated anyway

  1. Solomon KV et al. (2016) Early-branching gut fungi possess a large, comprehensive array of biomass-degrading enzymes. Science 351(6278): 1192-1195.
  2. Uesono Y et al. (2016) Local anesthetics and antipsychotic phenothiazines interact nonspecifically with membranes and inhibit hexose transporters in yeast. Genetics 202: 997-1012.
  3. Huthison CA et al. (2016) Design and synthesis of a minimal bacterial genome. Science 351(6280); 1414, aad6253-1-11
  4. Hamza A et al. (2015) Complementation of yeast genes with human genes as an experimental platform for functional testing of human genetic variants. Genetics 201: 1263-1274.
  5. Piccirillo S et al. (2015) Cell differentiation and spatial organization in yeast colonies: role of cell-wall integrity pathway. Genetics 201:1427-1438.

Emily

  1. Hose et al. (2015) Dosage compensation can buffer copy-number variation in wild yeast. eLife 2015;4:e05462
  2. Torres et al. (2016) No current evidence for widespread dosage compensation in S. cerevisiae. eLife 2016;5:e10996
  3. Gasch et al. (2016) Further support for aneuploidy tolerance in wild yeast and effects of dosage compensation on gene copy-number evolution. eLife 2016;5:e14409
  4. Barbosa et al. (2016) Evidence of Natural Hybridization in Brazilian Wild Lineages of Saccharomyces cerevisiae. Genome Biol Evol (2016) 8 (2):317-329.
  5. Lee et al. (2016) Multi-locus Genotypes Underlying Temperature Sensitivity in a Mutationally Induced Trait.PLoS Genet 12(3): e1005929. doi:10.1371/ journal.pgen.1005929
  6. Shapiro BJ, Leducq JB, Mallet J. (2016) What Is Speciation? PLoS Genet 12(3): e1005860

Jacek

  1. Shaw DM, Erren TC. Ten Simple Rules for Protecting Research Integrity. PLOS Comput Biol. 2015 Oct 1;11(10):e1004388.
  2. Steffensen JL, Dufault-Thompson K, Zhang Y. PSAMM: A Portable System for the Analysis of Metabolic Models. PLoS Comput Biol. 2016 Feb;12(2):e1004732.
  3. McAvoy A, Hauert C. Asymmetric Evolutionary Games. PLOS Comput Biol. 2015 Aug 26;11(8):e1004349.
  4. Chao L, Rang CU, Proenca AM, Chao JU. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation. PLoS Comput Biol. 2016 Jan;12(1):e1004700.
  5. Jobb G, von Haeseler A, Strimmer K. Retraction Note: TREEFINDER: a powerful graphical analysis environment for molecular phylogenetics. BMC Evolutionary Biology. 2015;15:243.

Peris

  1. Phylogenomics reveals three sources of adaptive variation during a rapid radiation. James B. Pease et al. 2016 PloS Biology
  2. The Hologenome Concept: Helpful or Hollow? Nacy Moran and Daniel Sloan 2016 PloS Biology
  3. PHYLUCE is a software package for the analysis of conserved genomic loci. Faircloth 2016 Bioinformatics
  4. SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data. Nelson et al 2016 Bioinformatics
  5. msa: an R package for multiple sequence alignment. Bonderhofer et al 2016. Bioinformatics
  6. Tools recommended to explore: BioPartsBuilder, IBS, HYBRIDSPADES, BRAKER1

Quinn

  1. Clowers et al. (2015) A unique ecological niche fosters hybridization of oak- tree and vineyard isolates of Saccharomyces cerevisiae. Mol. Ecol.
  2. Roop et al. (2016). Polygenic evolution of a sugar specialization trade-off in yeast. Nature
  3. Corcoran et al. (2016) Introgression maintains the genetic integrity of the mating-type determining chromosome of the fungus Neurospora tetrasperma. Genome Res
  4. Sun et al. (2016) An extended set of yeast-based functional assays accurately identifies human disease mutations. Genome Res.
  5. Machado et al. (2016) Comparative population genomics of latitudinal variation in Drosophila simulans and Drosophila melanogaster. Mol. Ecol.

Kelly

1. Chidi et al. (2016). Identifying and assessing the impact of wine acid-related genes in yeast. http://www.ncbi.nlm.nih.gov/pubmed/26040556 (Current Genetics)

Russell -


 

Friday, September 25, 2015 - participants are listed alphabetically and the articles they brought to the discussion as they provided them.

Bill: Pubmed ID's below

  1. 25756291

  2. 25913499

  3. 25594225

  4. 25686303

  5. 25742460

Christina:
  1. Evolution of ecological dominance of yeast species in high-sugar environments, Justin Fay lab,Evolution

  2. Toward a trophic theory of species diversity, John Terborgh, PNAS

  3. The adaptive radiation of lichen-forming Teloschistaceae is associated with sunscreening pigments and a bark-to-rock substrate shift, Gaya et al., PNAS

  4. Extrachromosomal circular DNA is common in yeast, Moller et al., PNAS

  5. Homeostasis and the glycogen shunt explains aerobic ethanol production in yeast
    Shulman et al. PNAS

Dana:
  1. Gene expression during zombie ant biting behavior reflects the complexity underlying fungal parasitic behavior manipulation – Bekker et al (2015) BMC Genomicshttp://www.biomedcentral.com/content/pdf/s12864-015-1812-x.pdf 
    Background: Parasites have evolved the ability to manipulate host behavior. 
    This paper describes the gene expression in the complex manipulator O. unilateralis s.l. and itsCamponotus ant host. 
    Methods: Ants’ heads were collected during and after (ants dead) biting behavior. Also, included were healthy ants and fungus in an insect cell culture media. 
    Sequenced genomes of O. unilateralis and gene expression was quantified for healthy ants, control fungal cultures and infected ants (two time points). 
    Results: Found the manipulated biting and time of death were synchronized. 
    o   13% of all putative proteins were novel to O. unilateralis 
    o   34 genes that were found contained 1 or more enterotoxin_a PFAM domains. §  9/34 were homologs to cholera toxins and the rest were heat labile enterotoxin_a.      
    Gene Expression results: 
    o   ½ of the tissue inside the head of an infected ant was from the ant host during biting. After biting 75% was the fungi, however this could be caused by the dying ant expressing fewer genes. 
    o   In the fungus, there is a shift in genes that are expressed during and after biting, for example, sugar metabolism is down regulated during biting and then upregulated once the ant has died and the fungus is actively growing. 
    o   In the host, there is an upregulation of genes related to apoptosis and a down regulation of immune response and stress genes. 
    o   They also found an upregulation of a whole subset of genes that would potentially be affecting behavior in the ant, for example, dopamine metabolism and protein-tyrosine phosphatase which are though to affect biting and locomotion. 
    o   These results suggest that the fungus is regulating/manipulating gene expression in the ants.  
  2. Influence of land use, nutrients, and geography of microbial communities and fecal indicator abundance in Lake Michigan beaches – Cloutier et al. (2015) AEM http://aem.asm.org/content/81/15/4904.full.pdf+htmlBackground   
    Wanted to determine what drives microbial community structure in Lake Michigan beaches. 
    Methods: Quantified species diversity of microbes at 8 Lake Michigan beaches across multiple beach zones (including water, berm and backshore). And measured factors that could influence species community structure, distance to water, nutrient levels, and distance from urban locations. 
    Results: Wisconsin beaches contain more E. coli and enterococci in the beach water than Michigan. 
    There is more bacteria in in the sand than in the water, but they are correlated. 
    Different beach zones have different microbial communities. 
    o   Sand communities are more diverse than water communities and diversity increases as distance from the water increases. 
    o   Comparisons within a beach zone across sites show high similarities in microbial communities; the largest differences among beach zone were among states. 
    §  They suggest states differences could be the result of 
    ·       Biogeography (community assemblages are similar over space and time) –fine scale sequencing distinguished the state two populations 
    ·       Local environment or physical conditions <- this is more likely because nutrient availability was the driving force of community of structure; which varied among geographic locations 
  3. Quantifying non-additive selection caused by indirect ecological effects – TerHorst et al. (2015) Ecologyhttp://www.esajournals.org/doi/pdf/10.1890/14-0619.1 
    Background:  Non-additive effects occur when indirect effects alter the strength or direction of selection that one species imposes on another. This can either constrain or augment the rate of adaptation to any one particular interacting species. 
    This paper suggests a statistical framework for quantifying the strength of nonadditive selection due to indirect ecological effects relative to pairwise selection. 
    Results: Use an ANCOVA to determine whether nonadditive selection was significant.
    Found that nonadditive selection caused by indirect ecological effects may be common in nature. 
    o   They looked at Herbivore X PlantA X PlantB interaction – while there was nonaddtive selection it was weak and did not affect the strength of pairwise selection. 
    o   Multiple pollinator example – they found an interaction among pollinators and this weakened selection imposed by individual pollinators. 
  4. The role of the microbiome of truffles in aroma formation: a meta-analysis approach – Vahdatzadeh et al. (2015) Applied and Environmental Microbiology http://aem.asm.org/content/81/20/6946.full.pdf+htmlBackground 
    Diverse microbial communities colonize truffle fruiting bodies – bacteria, yeast, other fungi, and viruses. 
    Major Results: Common odorants might be a mix of truffle and microbial origins, while less common odorants are derived from microbes only – with bacteria being the most important. 
    Microbial communities will differ depending on the life cycle stage of the truffle and truffle maturity. 
    Yeast communities may not represent the actual diversity because of enrichment methods, but they found: o   Cryptococcus albidus and C. humicola 
    o   Rhodoturula mucilaginosa 
    o   Debaryomyces hansenii 
    o   Saccharomyces paradoxus 
    They have a really cool heat map of flavors and the organisms that contribute those flavors.
  5. Variability among individuals is generated at the gene expression level – Peck et al. (2015) Ecologyhttp://www.esajournals.org/doi/pdf/10.1890/14-0726.1 
    Background: Want to determine how variation is generated and distributed across traits and at which scale there is the most variability 
    Methods: Compare levels of variation among individuals, or two Antarctic mollusks, in: 
    Gene expression
    Physiology
    Morphology 
    Results 
    Found the most variation in gene expression followed by physiological measures and the least in morphology. This suggests that variability is generated at the gene expression level. 
    As far as I can tell the only important contribution of this paper is a novel use for the Wentworth scale, which is a unit-less scale used to measure grain size in sediments. 
Drew:
  1. Galanie S et al. (2015). Complete biosynthesis of opioids in yeast. Science 349:1095-100. 
  2. Starita LM et al. (2015). Massively Parallel Functional Analysis of BRCA1 RING Domain Variants. Genetics200:413-422 
  3. Gao Z et al. (2015). An estimate of the average number of recessive lethal mutations carried by humans. Genetics 199:1243-1254. 
  4. Kelkar YD, Phillips DS & Ochman H (2015). Effects of Genic Base Composition on Growth Rate in G+ C-Rich Genomes. G3: Genes | Genomes | Genetics 5:1247-1252. 
  5. Matuszewski S, Hermisson J & Kopp M (2015). Catch Me if You Can: Adaptation from Standing Genetic Variation to a Moving Phenotypic Optimum. Genetics 200:1255-1274. 
Emily:
  1. A simple biophysical model emulates budding yeast chromosome condensation 


  2. Selection against Heteroplasmy Explains the Evolution of Uniparental Inheritance of Mitochondria     
  3. Molecular Clock of Neutral Mutations in a Fitness-Increasing Evolutionary Process 
  4. A Genetic Incompatibility Accelerates Adaptation in Yeast 
  5. Human evolution: The many mysteries of Homo naledi 
  6. Homo naledi, a new species of the genus Homo from the Dinaledi Chamber, South Africa 
  7. Geological and taphonomic context for the new hominin species Homo naledi from the Dinaledi Chamber, South Africa 

Jacek: 

5. Ferrante E, Turgut AE, Duéñez-Guzmán E, Dorigo M, Wenseleers T. Evolution of Self-Organized Task Specialization in Robot Swarms. PLoS Comput Biol. 2015 Aug 6;11(8):e1004273. 
4. Lovell D, Pawlowsky-Glahn V, Egozcue JJ, Marguerat S, Bähler J. Proportionality: A Valid Alternative to Correlation for Relative Data. PLoS Comput Biol. 2015 Mar 16;11(3):e1004075. 
3. Visser MD, McMahon SM, Merow C, Dixon PM, Record S, Jongejans E. Speeding Up Ecological and Evolutionary Computations in R; Essentials of High Performance Computing for Biologists. PLoS Comput Biol. 2015 Mar 26;11(3):e1004140. 
2. Roberts RJ. Ten Simple Rules to Win a Nobel Prize. PLoS Comput Biol. 2015 Apr 2;11(4):e1004084. 
1. Dutilleul M, Bonzom J-M, Lecomte C, Goussen B, Daian F, Galas S, et al. Rapid evolutionary responses of life history traits to different experimentally-induced pollutions in Caenorhabditis elegans. BMC Evol Biol. 2014 Dec 10;14(1):1–14. 

Peris:

  1. The fitness consequences of aneuploidy are driven by condition-dependent gene effects
    http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002155
  2. Beyond bar and line graphs: time for a new data presentation paradigm
    http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002128
  3. PopGeV: a web-based large-scale population genome browser
    http://bioinformatics.oxfordjournals.org/content/31/18/3048.long
  4. kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome
    http://bioinformatics.oxfordjournals.org/content/31/17/2877
  5. Big Data: Astronomical or Genomical?
    http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002195

Quinn: 
  1. A population genomics insight into the Mediterranean origins of wine yeast domestication

    Almedia, et al. Molecular Ecology http://www.ncbi.nlm.nih.gov/pubmed/26248006
  2. Comparative analyses of clinical and environmental populations of Cryptococcus neoformans in Botswana

    Chen, et al. Molecular Ecology http://www.ncbi.nlm.nih.gov/pubmed/26053414
  3. Population genomics of Bronze Age Eurasia

    Allentof, et al. Nature http://www.ncbi.nlm.nih.gov/pubmed/26062507
  4. A recent bottleneck of Y chromosome diversity coincides with a global change in culture

    Karmin, et al. Genome Research http://www.ncbi.nlm.nih.gov/pubmed/25770088
  5. The octopus genome and the evolution of cephalopod neural and morphological novelties

    Albertin, et al. Nature http://www.ncbi.nlm.nih.gov/pubmed/26268193


Friday, April 10, 2015 - participants are listed alphabetically and the articles they brought to the discussion are listed as they provided them.

William Alexander - reviews Cell and ACS Synthetic Biology

Emily Baker - reviews PloS Genetics and eLife Science

  1. PLoS Genetics: Rapid Evolution of Recombinant Saccharomyces cerevisiae for Xylose Fermentation through Formation of Extra- chromosomal Circular DNA - Mekonnen M. Demeke1,2, María R. Foulquié-Moreno1,2, Françoise Dumortier1,2, Johan M. Thevelein1,2*
  2. PLoS Genetics: Reproductive Isolation of Hybrid Populations Driven by Genetic Incompatibilities - Molly Schumer1*, Rongfeng Cui2,3,4, Gil G. Rosenthal2,3, Peter Andolfatto1,5
  3. eLIFE: Titles and abstracts of scientific reports ignore variation among species - BARBARA R MIGEON*
  4. eLIFE: THE NATURAL HISTORY OF MODEL ORGANISMS, The fascinating and secret wild life of the budding yeast S. cerevisiae – Gianni Liti

Drew Doering - reviews G3 and Genetics

  1. Margres et al. (2015) Contrasting Modes and Tempos of Venom Expression Evolution in Two Snake Species. Genetics 199(1) 165-176.
    -- The authors did transcriptomics and proteomics in a quantitative approach to measuring the various components of snake venom in eastern diamondback rattlesnakes (Crotalus adamanteus) and eastern coral snakes (Micrurus fulvius). They find that diamondback snake venom varies widely by population within Florida - likely due to an evolutionary arms race with specific prey - which makes development of antivenoms difficult. By contrast, they find that coral snake venom varies little between populations, suggesting either a recent range expansion or species-wide selective sweep and indicating that developing a single antivenom may be more feasible for this species than previously thought.
  2. Gerling et al. (2015) Dynamic DNA devices and assemblies formed by shape-complementary, non–base pairing 3D components. Science 347(6229) 1446-1452.
    -- The authors demonstrate the assembly of 3D objects using base-stacking (rather than base-pairing) DNA origami. They make an actuator, a switchable gear, an unfoldable nanobook, and a nanorobot.
  3. Sirr et al. (2015) Allelic Variation, Aneuploidy, and Nongenetic Mechanisms Suppress a Monogenic Trait in Yeast. Genetics 199(1) 247-262.
    -- The authors develop a new method called FACS-QTL which allows you to make large numbers of recombinant progeny that can then be subject to extreme selection conditions. They use this method to study a yeast model of human galactosemia, which involves a loss-of-function mutation in the GALT gene, which is the human homolog of yeast GAL7.
  4. Yang et al. (2014) Spatial Localization of Recent Ancestors for Admixed Individuals. G3 4(12) 2505-2518.
    -- The authors link geography and genetic variation of recent human generations to predict geographical origins of multiple recent ancestors for individuals with recent mixed ancestry.
  5. Borneman AR and Pretorius IS (2015) Genomic Insights into the Saccharomyces sensu stricto Complex. Genetics 199(2) 281-291.
    -- Another new Saccharomyces genus review that makes use of recent genomic data (including those by our own lab) to discuss the evolutionary history of the genus including domestication.

Meihua (Christina) Kuang - reviews PNAS and MBE

  1. Galactose metabolic genes in yeast respond to a ratio of galactose and glucose. Escalante-Chong, Renan, et al. Proceedings of the National Academy of Sciences (2015): 201418058.
    1. Short summary: Previously, it is believed that, in Scer, GAL genes are not repressed by glucose only when glucose concentrations are below a threshold. In contrast, this group found that, within a certain range, GAL genes induction occurs at a constant ratio of galactose and glucose concentrations. Based on their set up, this occurs when glucose is below 0.5% and galactose is above 0.006% (6x10-3). The mechanism is through the passive transportation of HXTs but not GAL2. This sensing provides fitness.
  2. Evolutionary Advantage Conferred by an Eukaryote-to-Eukaryote Gene Transfer Event in Wine Yeasts. Marsit, Souhir, et al. Molecular biology and evolution (2015): msv057.
    1. Short summary: 65 kb insertion present in many wine yeast strains, which is called region C. This region contains an active fructose transporter gene FSY1. They found this region is transferred from Torulaspora microellipsoides. 158 kb insertion, gene loss -> 65 kb subtelomeric region, formed by homologous recombination through a stretch of polyT sequence present at both Scer and Torulaspora microellipsoides. They also found gene conversion happened in this region. Two genes are conserved across all species carrying this region: FOT1-2, which encode oligopeptide tranporters. Deleting these two genes results in lower fitness in fermenting Chardonnay grape must. These two genes probably help to utilize abundant oxidized form of glutathione in the must and also other nitrogen source. Glutathione is important in a wide range of stress response, such as oxidative stress caused by reactive oxygen species.
  3. Quantitative Description of a Protein Fitness Landscape Based on Molecular Feature. Meini, María-Rocío, et al. Molecular biology and evolution (2015): msv059.
    1. Short summary: How the evolutionary trajectories of favorable mutations are constrained with each others. Their previous work found four favorable mutations in this enzyme, metallo-beta-lactamases, can give rise to high resistance to an antibiotic cephalexin. They constructed all possible 16 combinations of variants, measure the resistance. They found sign epistasis limit the accessible trajectory. They characterize multiple biochemical features of the enzymes. They found different favorable mutations give rise to different favorable biochemical features and at the same time can lower the fitness of other features. For example, the most favorable mutation to catalytic efficiency decrease protein stability. Other favorable mutations compensate for this loss. The mutation increasing co-factor binding affinity decreases catalytic efficiency.
  4. Integrity of the yeast mitochondrial genome, but not its distribution and inheritance relies on mitochondrial fission and fusion. Osman, Christof, et al. Proceedings of the National Academy of Sciences 112.9 (2015): E947-E956.
    1. Short summary: They developed a novel approach to non invasively label mtDNA in live cells. This news had appeared in SGD for while. They can monitor how mitochondria are inherited during cell division. Fusion and fission of mitochondria are required to maintain the integrity of mitochondria but not their inheritance and spatial distribution. Paired sequencing shows that mt genome rearragement is greatly increased in the mutant. Most rearrangements are surrounding the replication origins.
  5. Plasticity and epistasis strongly affect bacterial fitness after losing multiple metabolic genes. D'Souza, Glen, et al. Evolution (2015).
    1. Short summary: They computationally analyze 1432 eubacterial metabolic networks. Most pairs of auxotrophies co-occurred significantly more often than expected by chance. This associates with epistatic interactions and their habitats. This is consistent with the previous idea that selective benefits drive the loss of biosynthetic functions when certain metabolites are sufficiently available in the environment.

Quinn Langdon - reviews Mol. Ecol. and Genome Res. and Nature

  1. Cahill, J. a., I. Stirling, L. Kistler, R. Salamzade, E. Ersmark, T. L. Fulton, M. Stiller, R. E. Green, and B. Shapiro. 2014. Genomic evidence of geographically widespread effect of gene flow from polar bears into brown bears. Mol. Ecol. 24:1205 –1217.
  2. Kowallik, V., E. Miller, and D. Greig. 2015. The interaction of Saccharomyces paradoxus with its natural competitors on oak bark. Mol. Ecol. 24:1596–610.
  3. Lamichhaney, S., J. Berglund, M. S. Almén, K. Maqbool, M. Grabherr, A. Martinez-Barrio, M. Promerová, C.-J. Rubin, C. Wang, N. Zamani, B. R. Grant, P. R. Grant, M. T. Webster, and L. Andersson. 2015. Evolution of Darwin’s finches and their beaks revealed by genome sequencing. Nature 518:371–5.
  4. Levy, S. F., J. R. Blundell, S. Venkataram, D. A. Petrov, D. S. Fisher, and G. Sherlock. 2015. Quantitative evolutionary dynamics using high-resolution lineage tracking. Nature 519:181–6.

Peris Navarro - reviews PloS Biol and Bioinf

  • Wang,J., Atolia, E., Hua, B., Savir, Y., Escalante-Chong, R., Springer, M. (2015). Natural variation in preparation for nutrient depletion reveals a cost-benefit tradeoff. PLoS Biol, 13, e1002041
Strain diversity in S. cerevisiae is translated in differences in the response to glu and galactose mixed mediums with important tradeoff and consequences to compete with other strains.
  • Sato,P.M., Yoganathan, K., Jung, J. H., Peisajovich, S. G. (2014). The robustness of a signaling complex to domain rearrangements facilitates network evolution. PLoS Biol, 12, e1002012
Protein domain rearrangements of signaling pathways are robust and might allow the exploration of the genotypic landscape
  • Priebe,S., Kreisel, C., Horn, F., Guthke, R., Linde, J. (2014). FungiFun2: a comprehensive online resource for systematic analysis of gene lists from fungal species. Bioinformatics
A database with 298 strains of 240 species for making go term enrichment analysis for fungal genomes.

  • Dall'Olio,G.M., Vahdati, A. R., Bertranpetit, J., Wagner, A., Laayouni, H. (2015). VCF2Networks: applying genotype networks to single-nucleotide variants data. Bioinformatics, 31, 438-439.
A tool that allows to reconstruct genotype network analysis to single nucleotide variants and associate a given phenotype to the network or infer robustness or evolvavility of determine genotypes.
  • Wu,Y. (2015). A coalescent-based method for population tree inference with haplotypes. Bioinformatics, 31, 691-698.
A program that reconstruct the population tree from picking individuals and their corresponding haplotypes.

 

Kayla Sylvester - reviews FEMS Yeast and Electron J Biotechnol

  1. Hebly M, Brickwedde a., Bolat I, Driessen MRM, de Hulster E a. F, van den Broek M, Pronk JT, Geertman J-M, Daran J-M & Daran-Lapujade P (2015) S. cerevisiae x S. eubayanus interspecific hybrid, the best of both worlds and beyond. FEMS Yeast Res 15: fov005–fov005.
  2. Kurtzman CP & Robnett CJ (2014) Description of Kuraishia piskuri f.a., sp. nov., a new methanol assimilating yeast and transfer of phylogenetically related Candida species to the genera Kuraishia and Nakazawaea as new combinations. FEMS Yeast Res 14: n/a – n/a.
  3. Moktaduzzaman M, Galafassi S, Capusoni C, Vigentini I, Ling Z, Pi kur J & Compagno C (2015) Galactose utilization sheds new light on sugar metabolism in the sequenced strain Dekkera bruxellensis CBS 2499. FEMS Yeast Res 15: fou009–fou009.
  4. Robert V, Cardinali G & Casadevall A (2015) Distribution and impact of yeast thermal tolerance permissive for mammalian infection. BMC Biol 13.

Friday, November 21, 2014 - participants are listed alphabetically and the articles they brought to the discussion are listed as they provided them.

William Alexander - reviews Cell and ACS Synthetic Biology

  1. Pagliuca FW, Millman JR, Gurtler M, Segel M, Van Dervort A, Ryu JH, Peterson QP, Greiner D, Melton DA. Generation of Functional Human Pacreatic beta Cells in vitro. Cell. 2014 Oct 9; 159(2): 428-39.
  2. Yi JJ, Wang H, Vilela M, Danuser G, Hahn K. Manipulation of Endogenous Kinase Activity in Living Cells Using Photoswitchable Inhibitory Peptides. ACS Synbth Biol. 2014 Nov 21; 3(11):788-95.
  3. Purcell O, Peccoud J, Lu TK. Rule-based design of synthetic transcription factors in eukaryotes. ACS Synth Biol. 2014 Oct 17; 3(10):737-44.

 

Emily Baker - reviews PloS Genetics and eLife Science

  1. Evolving a 24-hour oscillator in budding yeast.
  2. Accurate, Model-Based Tuning of Synthetic Gene Expression Using Introns in S. cerevisiae.
  3. Genetic Interactions Involving Five or More Genes Contribute to a Complex Trait in Yeast

Drew Doering - reviews G3 and Genetics

  1. DiPrima, S., Haarer, B., Viggiano, S., Pons, C., Myers, C. L., & Amberg, D. C. (2014). Linking genetics to structural biology: complex heterozygosity screening with actin alanine scan alleles identifies functionally related surfaces on yeast actin. G3 (Bethesda, Md.), 4(8), 1491–501. doi:10.1534/g3.114.012054
  2. Fazlollahi, M., Lee, E., Muroff, I., Lu, X.-J., Gomez-Alcala, P., Causton, H. C., & Bussemaker, H. J. (2014). Harnessing natural sequence variation to dissect posttranscriptional regulatory networks in yeast. G3 (Bethesda, Md.), 4(8), 1539–53. doi:10.1534/g3.114.012039
  3. Kelly, A. C., Busby, B., & Wickner, R. B. (2014). Effect of Domestication on the Spread of the [PIN+] Prion in Saccharomyces cerevisiae. Genetics, 197(3), 1007–24. doi:10.1534/genetics.114.165670
  4. Labunskyy, V. M., Suzuki, Y., Hanly, T. J., Murao, A., Roth, F. P., & Gladyshev, V. N. (2014). The insertion Green Monster (iGM) method for expression of multiple exogenous genes in yeast. G3 (Bethesda, Md.), 4(7), 1183–91. doi:10.1534/g3.114.010868
  5. Tulchinsky, A. Y., Johnson, N. a, Watt, W. B., & Porter, A. H. (2014). Hybrid Incompatibility Arises in a Sequence-Based Bioenergetic Model of Transcription Factor Binding. Genetics, 198(November), 1155–1166. doi:10.1534/genetics.114.168112

Meihua (Christina) Kuang - reviews PNAS and MBE

  1. Mating-type switching by chromosomal inversion in methylotrophic yeasts suggests an origin for the three-locus Saccharomyces cerevisiae system (PNAS)
    PMID: 25349420
    The mating type switching system of Saccharomycetaceae family is consist of three locus and Candida clade uses one locus switch. They found a clade next to Candida uses two locus switch and proposes that this is the ancestral state and more complex mating type switch system was formed afterwards
    Hansenula polymorpha and Pichia pastoris (methylotrophs) uses invertible region to do mating type switch (centromere do the silencing) relatively lower efficiency; higher efficiency mating type switch helps to sporulate earlier (simulation shows that more cells can be produced if more spores can be formed, which depends on how frequent the mating type switch).
  2. Domesticated transposase Kat1 and its fossil imprints induce sexual differentiation in yeast (PNAS)
    PMID: 25313032
    A transposase Kat1 is domesticated in Klac to act as the function of HO. Kat acts on inverted repeat. It is induced through nutrient limitation and normally can’t be well translated due to the frameshift by the presence of slippery sequence. Kat1 is specific to Klu clade.
  3. The Genotype–Phenotype Map of Yeast Complex Traits: Basic Parameters and the Role of Natural Selection (MBE)
    PMID: 24723420
    Conclusions: Their results support that natural selection favors genetic robustness and environmental robustness by genotype-phenotype map (GPM) based on the data from previous high-throughput studies. Two models. Most traits are affected by more small effect genes than large effect genes. The more important a trait is, the more robust it is to environmental stochastic or mutations (effect size of each gene).
  4. Comparative Genomics as a Time Machine: How Relative Gene Dosage and Metabolic Requirements Shaped the Time-dependent Resolution of Yeast Polyploidy (MBE)
    PMID: 25158798
    1st stage: DNA repair, organelles (mt); 2nd stage: dosage (PPI, loss); 3rd stage: TF and high-flux enzymes
  5. Ecological transition predictably associated with gene degeneration (MBE)
    PMID: 25371436
    blue to red flower changes
    Penstemon genus
    nonpleiotropic genes are probably lost easier

Quinn Langdon - reviews Mol. Ecol. and Genome Res. and Nature

  1. Antoniazza, S., R. Kanitz, S. Neuenschwander, R. Burri, A. Gaigher, A. Roulin, and J. Goudet. 2014. Natural selection in a post-glacial range expansion: the case of the colour cline in the European barn owl. Mol. Ecol. 1–16.
  2. Enard, D., P. W. Messer, and D. a Petrov. 2014. Genome-wide signals of positive selection in human evolution. Genome Res. 24:885–95.
  3. Keane, O. M., C. Toft, L. Carretero-Paulet, G. W. Jones, and M. a Fares. 2014. Preservation of genetic and regulatory robustness in ancient gene duplicates of Saccharomyces cerevisiae. Genome Res. 1830–1841.
  4. Robinson, J. D., L. Bunnefeld, J. Hearn, G. N. Stone, and M. J. Hickerson. 2014. ABC inference of multi-population divergence with admixture from unphased population genomic data. Mol. Ecol. 23:4458–71.
  5. Romiguier, J., P. Gayral, M. Ballenghien, a. Bernard, V. Cahais, a. Chenuil, Y. Chiari, R. Dernat, L. Duret, N. Faivre, E. Loire, J. M. Lourenco, B. Nabholz, C. Roux, G. Tsagkogeorga, a. a.-T. Weber, L. a. Weinert, K. Belkhir, N. Bierne, S. Glémin, and N. Galtier. 2014. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature, doi: 10.1038/nature13685.

Peris Navarro - reviews PloS Biol and Bioinf

  1. The Genomic Landscape of Compensatory Evolution
    PMID: 25157590
  2. COSMOS: Python library for massively parallel worflows (Bioinf)
    PMID: 24982428
  3. Transient hypermutagenesis accelerates the evolution of Legume endosymbionts following Horizontal Gene Transfer
    PMID: 25181317
  4. deML: Robust demultiplexing of Illumina sequences using a likelihood-based approach
    PMID: 25359895
  5. Shiny-phyloseq: web application for interactive microbiome analysis with provenance tracking
    PMID: 25262154

Brandon Pfannenstiel - Rotator in the lab reviewed mBIO and Experimental Yeast Populations

  1. Anna M. Seekatz, Johannes Aas, Charles E. Gessert, et al. 2014. Recovery of the Gut Microbiome following Fecal Microbiota Transplantation. mBio 5(3): doi:10.1128/mBio.00893-14.
  2. Christopher E. Ellison, David Kowbel, N. Louise Glass, et al. 2014. Discovering Function of Unannotated Genes from a Transcriptome Survey of Wild Fungal Isolates. mBIO 5(2): doi:10.1128/mBio.01046-13.
  3. Linda M. Kohn, James B. Anderson. 2014. The Underlying Structure of Adaptation under Strong Selection in 12 Experimental Yeast Populations. 13(9): 1200. doi: 10.1128/EC.00122-14.

Kayla Sylvester - reviews FEMS Yeast and Electron J Biotechnol

  1. Francesca N, Carvalho C, Sannino C, Guerreiro M a, Almeida PM, Settanni L, Massa B, Sampaio JP & Moschetti G (2014) Yeasts vectored by migratory birds collected in the Mediterranean island of Ustica and description of Phaffomyces usticensis f.a. sp. nov., a new species related to the cactus ecoclade. FEMS Yeast Res 14: 910–921. http://www.ncbi.nlm.nih.gov/pubmed/24981278 (Accessed November 21, 2014).
  2. Rodríguez ME, Pérez-Través L, Sangorrín MP, Barrio E & Lopes C a (2014) Saccharomyces eubayanus and Saccharomyces uvarum associated with the fermentation of Araucaria araucana seeds in Patagonia. FEMS Yeast Res 14: 948–965. http://www.ncbi.nlm.nih.gov/pubmed/25041507 (Accessed November 21, 2014).
  3. Úbeda J, Maldonado Gil M, Chiva R, Guillamón JM & Briones A (2014) Biodiversity of non-Saccharomyces yeasts in distilleries of the La Mancha region (Spain). FEMS Yeast Res 14: 663–673. http://www.ncbi.nlm.nih.gov/pubmed/24656143 (Accessed November 21, 2014).
  4. Westman JO, Taherzadeh MJ & Franzén CJ (2012) Inhibitor tolerance and flocculation of a yeast strain suitable for second generation bioethanol production. Electron J Biotechnol 15. http://www.ejbiotechnology.info/index.php/ejbiotechnology/article/view/914 (Accessed November 21, 2014).
  5. Zaky AS, Tucker G a, Daw ZY & Du C (2014) Marine yeast isolation and industrial application. FEMS Yeast Res 14: 813–825. http://www.ncbi.nlm.nih.gov/pubmed/24738708 (Accessed November 8, 2014).

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Chris Todd Hittinger
Laboratory of Genetics
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4340-4360 Genetics/Biotechnology Center
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United States

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